AWS Lakehouse Platform Engineer Job at Riverflex (Abu Dhabi or Dubai)

Staff Backend Software Engineer - Partner Platform

Addepar is seeking a Staff Backend Software Engineer to join our Partner Platfor...

Location

United Kingdom , Edinburgh

Salary:

Not provided

Addepar

Expiration Date

Until further notice

Requirements

Strong programming experience (preferably in Python)
Solid background in databases and working with large datasets (e.g. Spark, other big data frameworks)
Excellent communication and cross-functional collaboration skills

Job Responsibility

Build scalable data integration pipelines that support mission-critical projects across the organization
Own and contribute to end-to-end engineering projects using the Addepar data lakehouse
Partner with stakeholders across analytics, operations, and product to deliver solutions that directly impact clients and business teams
Participate in the design, development, and optimization of tools and systems for account conversions, historical data imports, and embedded integrations
Maintain and expand the foundational codebase supporting the data lakehouse ecosystem

What we offer

Reasonable accommodation for individuals with disabilities
Commitment to equal opportunity and diversity
Global flexible workforce model

Staff /Sr Staff/ Principal Engineer - Lakehouse

Balbix is the world's leading platform for cybersecurity posture automation. Usi...

Location

India , Bangalore; Gurgaon

Salary:

Not provided

Balbix

Expiration Date

Until further notice

Requirements

8+ years of experience in backend software development dealing with large scale applications involving large scale data
Proven experience in defining and improving application design and architecture
Drive to discover and learn the required new technologies
Exposure to state of the art technologies for large scale data systems
Proficiency in programming languages such as Python, Scala or Java
Hands-on experience with large scale technologies such as Apache Spark, Apache Flink, Cassandra
Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform
Bachelor's or Master's degree in Computer Science, Engineering, or related field
Excellent problem-solving and analytical skills
Strong communication and collaboration skills

Job Responsibility

Collaborate with product managers, data scientists, and other stakeholders to understand requirements and translate them into technical solutions
Design, develop, and deploy high scale systems using state of the art technologies
Build reliable, consistent and high throughput data services and interfaces
Mentor junior developers and contribute to knowledge sharing within the team
Help define and ensure the best practices and guidelines across the systems
Optimize and tune applications for performance and scalability
Troubleshoot and resolve issues in production environments

Fulltime

Data Engineer III

As a Data Engineer, you will play a key role in designing, developing, and maint...

Location

India , Chennai

Salary:

Not provided

Arcadia

Expiration Date

Until further notice

Requirements

3+ years as a Data Engineer, data-adjacent Software Engineer, or a did-everything small data team member with a focus on building and maintaining data pipelines
Strong Python skills, especially in the context of data orchestration
Strong understanding of database management and design, including experience with Snowflake or an equivalent platform
Proficiency in SQL
Familiarity with data integration patterns, ETL/ELT processes, and data warehousing concepts
Experience with Argo, Prefect, Airflow, or similar data orchestration tools
Excellent problem-solving and analytical skills with a strong attention to detail
Ability to bring a customer-oriented and empathetic approach to understanding how data is used to drive the business
Strong communication skills

Job Responsibility

Design, develop, and maintain scalable and efficient data pipelines in an AWS environment, centered on our Snowflake instance and using Fivetran, Prefect, Argo, and dbt
Collaborate with business analysts, analytics engineers, and software engineers to understand data requirements and deliver reliable solutions
Design, build and maintain tooling that enables users and services to interact with our data platform, including CI/CD pipelines for our data lakehouse, unit/integration/validation testing frameworks for our data pipelines, and command-line tools for ad-hoc data evaluation
Identify and implement best practices for data ingestion, transformation, and storage to ensure data integrity and accuracy
Optimize and tune data pipelines for improved performance, scalability, and reliability
Monitor data pipelines and proactively address any issues or bottlenecks to ensure uninterrupted data flow
Develop and maintain documentation for data pipelines, ensuring knowledge sharing and smooth onboarding of new team members
Implement data governance and security measures to ensure compliance with industry standards and regulations
Keep up to date with emerging technologies and trends in data engineering and recommend their adoption as appropriate

What we offer

Competitive compensation based on market standards
Flexible Leave Policy
Office is in the heart of the city in case you need to step in for any purpose
Medical Insurance (1+5 Family Members)
We provide comprehensive coverage including accident policy and life Insurance
Annual performance cycle
Quarterly team engagement activities and rewards & recognitions
L&D programs to foster professional growth
A supportive engineering culture that values diversity, empathy, teamwork, trust, and efficiency

Fulltime

Senior Big Data Engineer

The Big Data Engineer is a senior level position responsible for establishing an...

Location

Canada , Mississauga

Salary:

94300.00 - 141500.00 USD / Year

Citi

Expiration Date

Until further notice

Requirements

5+ Years of Experience in Big Data Engineering (PySpark)
Data Pipeline Development: Design, build, and maintain scalable ETL/ELT pipelines to ingest, transform, and load data from multiple sources
Big Data Infrastructure: Develop and manage large-scale data processing systems using frameworks like Apache Spark, Hadoop, and Kafka
Proficiency in programming languages like Python, or Scala
Strong expertise in data processing frameworks such as Apache Spark, Hadoop
Expertise in Data Lakehouse technologies (Apache Iceberg, Apache Hudi, Trino)
Experience with cloud data platforms like AWS (Glue, EMR, Redshift), Azure (Synapse), or GCP (BigQuery)
Expertise in SQL and database technologies (e.g., Oracle, PostgreSQL, etc.)
Experience with data orchestration tools like Apache Airflow or Prefect
Familiarity with containerization (Docker, Kubernetes) is a plus

Job Responsibility

Partner with multiple management teams to ensure appropriate integration of functions to meet goals as well as identify and define necessary system enhancements to deploy new products and process improvements
Resolve variety of high impact problems/projects through in-depth evaluation of complex business processes, system processes, and industry standards
Provide expertise in area and advanced knowledge of applications programming and ensure application design adheres to the overall architecture blueprint
Utilize advanced knowledge of system flow and develop standards for coding, testing, debugging, and implementation
Develop comprehensive knowledge of how areas of business, such as architecture and infrastructure, integrate to accomplish business goals
Provide in-depth analysis with interpretive thinking to define issues and develop innovative solutions
Serve as advisor or coach to mid-level developers and analysts, allocating work as necessary
Appropriately assess risk when business decisions are made, demonstrating consideration for the firm's reputation and safeguarding Citigroup, its clients and assets, by driving compliance with applicable laws, rules and regulations, adhering to Policy, applying sound ethical judgment regarding personal behavior, conduct and business practices, and escalating, managing and reporting control issues with transparency

What we offer

Well-being support
Growth opportunities
Work-life balance support

Fulltime

Senior/Architect Data Engineer

We are seeking a highly skilled and experienced Senior/Architect Data Engineer t...

Location

Poland , Warsaw; Poznań; Lublin; Katowice; Rzeszów

Salary:

Not provided

Inetum

Expiration Date

Until further notice

Requirements

Proven experience architecting solutions on the Databricks Lakehouse using Unity Catalog, Delta Lake, MLflow, Model Serving, Feature Store, AutoML, and Databricks Workflows
Expertise in real-time/low latency model serving architectures with auto-scaling, confidence-based routing, and A/B testing
Strong knowledge of cloud security and governance on Azure or AWS, including Azure AD/AWS IAM, encryption, audit trails, and compliance frameworks
Hands-on MLOps skills across experiment tracking, model registry/versioning, drift monitoring, automated retraining, and production rollout strategies
Proficiency in Python and Databricks native tooling, with practical integration of REST APIs/SDKs and Databricks SQL in analytics products
Familiarity with React dashboards and human-in-the-loop operational workflows for ML and data quality validation
Demonstrated ability to optimize performance, reliability, and cost for large-scale analytics/ML platforms with strong observability
Experience leading multi-phase implementations with clear success metrics, risk management, documentation, and training/change management
Domain knowledge in telemetry, time series, or industrial data (aerospace a plus) and prior work with agentic patterns on Mosaic AI
Databricks certifications and experience in enterprise deployments of the platform are preferred

Job Responsibility

Lead the design and implementation of a Databricks-centric multi-agent processing engine
Design governed data ingestion, storage, and real-time processing workflows using Delta Lake, Structured Streaming, and Databricks Workflows
Own the model lifecycle with MLflow, including experiment tracking, registry/versioning, A/B testing, drift monitoring, and automated retraining pipelines
Architect low latency model serving endpoints with auto-scaling and confidence-based routing for sub-second agent decisioning
Establish robust data governance practices with Unity Catalog, including access control, audit trails, data quality, and compliance
Drive performance and cost optimization strategies, including auto-scaling, spot usage, and observability dashboards
Define production release strategies (blue-green), monitoring and alerting mechanisms, operational runbooks, and Service Level Objectives (SLOs)
Partner with engineering, MLOps, and product teams to deliver human-in-the-loop workflows and dashboards
Lead change management, training, and knowledge transfer while managing a parallel shadow processing path
Plan and coordinate phased delivery, success metrics, and risk mitigation

What we offer

Flexible working hours
Hybrid work model
Cafeteria system
Generous referral bonuses (up to PLN6,000)
Additional revenue sharing opportunities
Ongoing guidance from dedicated Team Manager
Tailored technical mentoring from assigned technical leader
Dedicated team-building budget for online and on-site team events
Opportunities to participate in charitable initiatives and local sports programs
Supportive and inclusive work culture

Fulltime

Principal Data Engineer

PointClickCare is searching for a Principal Data Engineer who will contribute to...

Location

United States

Salary:

183200.00 - 203500.00 USD / Year

PointClickCare

Expiration Date

Until further notice

Requirements

Principal Data Engineer with at least 10 years of professional experience in software or data engineering, including a minimum of 4 years focused on streaming and real-time data systems
Proven experience driving technical direction and mentoring engineers while delivering complex, high-scale solutions as a hands-on contributor
Deep expertise in streaming and real-time data technologies, including frameworks such as Apache Kafka, Flink, and Spark Streaming
Strong understanding of event-driven architectures and distributed systems, with hands-on experience implementing resilient, low-latency pipelines
Practical experience with cloud platforms (AWS, Azure, or GCP) and containerized deployments for data workloads
Fluency in data quality practices and CI/CD integration, including schema management, automated testing, and validation frameworks (e.g., dbt, Great Expectations)
Operational excellence in observability, with experience implementing metrics, logging, tracing, and alerting for data pipelines using modern tools
Solid foundation in data governance and performance optimization, ensuring reliability and scalability across batch and streaming environments
Experience with Lakehouse architectures and related technologies, including Databricks, Azure ADLS Gen2, and Apache Hudi
Strong collaboration and communication skills, with the ability to influence stakeholders and evangelize modern data practices within your team and across the organization

Job Responsibility

Lead and guide the design and implementation of scalable streaming data pipelines
Engineer and optimize real-time data solutions using frameworks like Apache Kafka, Flink, Spark Streaming
Collaborate cross-functionally with product, analytics, and AI teams to ensure data is a strategic asset
Advance ongoing modernization efforts, deepening adoption of event-driven architectures and cloud-native technologies
Drive adoption of best practices in data governance, observability, and performance tuning for streaming workloads
Embed data quality in processing pipelines by defining schema contracts, implementing transformation tests and data assertions, enforcing backward-compatible schema evolution, and automating checks for freshness, completeness, and accuracy across batch and streaming paths before production deployment
Establish robust observability for data pipelines by implementing metrics, logging, and distributed tracing for streaming jobs, defining SLAs and SLOs for latency and throughput, and integrating alerting and dashboards to enable proactive monitoring and rapid incident response
Foster a culture of quality through peer reviews, providing constructive feedback and seeking input on your own work

What we offer

Benefits starting from Day 1!
Retirement Plan Matching
Flexible Paid Time Off
Wellness Support Programs and Resources
Parental & Caregiver Leaves
Fertility & Adoption Support
Continuous Development Support Program
Employee Assistance Program
Allyship and Inclusion Communities
Employee Recognition … and more!

Fulltime

New

Solutions Director, Analytics & AI

Rackspace is seeking a highly accomplished Solution Director, Analytics & AI to ...

Location

United States

Salary:

202100.00 - 355410.00 USD / Year

Rackspace

Expiration Date

Until further notice

Requirements

Deep experience with generative AI technologies: Amazon Bedrock, Amazon Q, LLM architectures, RAG implementations
Proven track record delivering data modernization: Lakehouse architectures, Databricks and/or Snowflake implementations, AWS Glue/EMR deployments
At least 5 years as a senior-level architect or solutions leader with hands-on experience in both AI/ML and data platform modernization
Demonstrated success engaging C-level executives using generative AI demonstrations while delivering complex data platform transformations
Strong understanding across the full spectrum: AI/ML: Generative AI, foundation models, LLMs, traditional ML, prompt engineering, fine-tuning
Data Platforms: Lakehouse architectures, data mesh, ETL/ELT, streaming, data governance, data quality
Proficiency in Python, SQL, and Spark with hands-on experience in: Generative AI: LangChain, vector databases, embedding models
Data Engineering: PySpark, Apache Iceberg/Delta Lake, orchestration tools
Proven ability to articulate both visionary AI possibilities and practical data platform requirements to diverse audiences
Bachelor’s degree in computer science, Data Science, Engineering, Mathematics, or related technical field

Job Responsibility

Drive top-of-funnel opportunity creation through two parallel tracks: engaging C-level stakeholders with generative AI demonstrations (Amazon Q, Amazon Bedrock) and identifying data modernization needs for Lakehouse transformations
Lead the design and architecture of dual solution portfolios: Generative AI Solutions: Amazon Bedrock implementations, Amazon Q deployments, QuickSight with Q capabilities, RAG architectures, and custom LLM solutions
Data Modernization: Enterprise Lakehouse architectures using AWS Glue, SageMaker Unified Studio, Databricks on AWS, and Snowflake on AWS
Act as the trusted advisor positioning generative AI as the transformational vision while grounding delivery in robust data platform modernization
Develop compelling business cases that connect AI aspirations with practical data foundation requirements, demonstrating ROI across both portfolios
Stay current with advancements in generative AI (foundation models, LLMs) and modern data architectures (Lakehouse patterns, data mesh, unified analytics)
Contribute to Rackspace intellectual property through reference architectures covering both generative AI implementations and Lakehouse design patterns
Serve as the primary technical executive orchestrating both generative AI discussions and data modernization programs for strategic accounts
Build strategic relationships using two engagement models: Executive Level: Amazon Q demonstrations, QuickSight analytics with generative BI, art-of-the-possible sessions
Technical Level: Lakehouse architecture workshops, platform assessments (Databricks vs Snowflake vs AWS-native), migration planning

What we offer

Opportunity to lead dual portfolios at the intersection of generative AI innovation and data platform modernization
Direct engagement with C-level executives on transformational initiatives
Access to latest AWS technologies across AI and data services
Work with leading platforms: Databricks, Snowflake, AWS native services
Comprehensive professional development and certification support
Competitive compensation and benefits package

Fulltime

New

Solutions Director - Analytics & AI

Rackspace is seeking a highly accomplished Solution Director, Analytics & AI to ...

Location

United Kingdom

Salary:

Not provided

Rackspace

Expiration Date

Until further notice

Requirements

Deep experience with generative AI technologies: Amazon Bedrock, Amazon Q, LLM architectures, RAG implementations
Proven track record delivering data modernization: lakehouse architectures, Databricks and/or Snowflake implementations, AWS Glue/EMR deployments
At least 5 years as a senior-level architect or solutions leader with hands-on experience in both AI/ML and data platform modernization
Demonstrated success engaging C-level executives using generative AI demonstrations while delivering complex data platform transformations
Strong understanding across the full spectrum: AI/ML: Generative AI, foundation models, LLMs, traditional ML, prompt engineering, fine-tuning
Data Platforms: Lakehouse architectures, data mesh, ETL/ELT, streaming, data governance, data quality
Proficiency in Python, SQL, and Spark with hands-on experience in: Generative AI: LangChain, vector databases, embedding models
Data Engineering: PySpark, Apache Iceberg/Delta Lake, orchestration tools
Proven ability to articulate both visionary AI possibilities and practical data platform requirements to diverse audiences
Bachelor's degree in Computer Science, Data Science, Engineering, Mathematics, or related technical field

Job Responsibility

Strategic Leadership & Opportunity Development: Drive top-of-funnel opportunity creation through two parallel tracks: engaging C-level stakeholders with generative AI demonstrations (Amazon Q, Amazon Bedrock) and identifying data modernization needs for lakehouse transformations
Lead the design and architecture of dual solution portfolios: Generative AI Solutions, Amazon Bedrock implementations, Amazon Q deployments, QuickSight with Q capabilities, RAG architectures, and custom LLM solutions
Data Modernization: Enterprise lakehouse architectures using AWS Glue, SageMaker Unified Studio, Databricks on AWS, and Snowflake on AWS
Act as the trusted advisor positioning generative AI as the transformational vision while grounding delivery in robust data platform modernization
Develop compelling business cases that connect AI aspirations with practical data foundation requirements, demonstrating ROI across both portfolios
Stay current with advancements in generative AI (foundation models, LLMs) and modern data architectures (lakehouse patterns, data mesh, unified analytics)
Contribute to Rackspace intellectual property through reference architectures covering both generative AI implementations and lakehouse design patterns
Customer Engagement & Solution Delivery: Serve as the primary technical executive orchestrating both generative AI discussions and data modernization programs for strategic accounts
Build strategic relationships using two engagement models: Executive Level: Amazon Q demonstrations, QuickSight analytics with generative BI, art-of-the-possible sessions
Technical Level: Lakehouse architecture workshops, platform assessments (Databricks vs Snowflake vs AWS-native), migration planning

Fulltime

AWS Lakehouse Platform Engineer

Riverflex

Location:
United Arab Emirates , Abu Dhabi or Dubai

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

Job Description:

Job Responsibility:

Requirements:

Additional Information:

Job Posted:
January 10, 2026

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