Cloud Engineer, Data Processing Job at Aptiv plc (Monterrey)

Cloud Technical Architect / Data DevOps Engineer

The role involves designing, implementing, and optimizing scalable Big Data and ...

Location

United Kingdom , Bristol

Salary:

Not provided

Hewlett Packard Enterprise

Expiration Date

Until further notice

Requirements

An organised and methodical approach
Excellent time keeping and task prioritisation skills
An ability to provide clear and concise updates
An ability to convey technical concepts to all levels of audience
Data engineering skills – ETL/ELT
Technical implementation skills – application of industry best practices & designs patterns
Technical advisory skills – experience in researching technological products / services with the intent to provide advice on system improvements
Experience of working in hybrid environments with both classical and DevOps
Excellent written & spoken English skills
Excellent knowledge of Linux operating system administration and implementation

Job Responsibility

Detailed development and implementation of scalable clustered Big Data solutions, with a specific focus on automated dynamic scaling, self-healing systems
Participating in the full lifecycle of data solution development, from requirements engineering through to continuous optimisation engineering and all the typical activities in between
Providing technical thought-leadership and advisory on technologies and processes at the core of the data domain, as well as data domain adjacent technologies
Engaging and collaborating with both internal and external teams and be a confident participant as well as a leader
Assisting with solution improvement activities driven either by the project or service
Support the design and development of new capabilities, preparing solution options, investigating technology, designing and running proof of concepts, providing assessments, advice and solution options, providing high level and low level design documentation
Cloud Engineering capability to leverage Public Cloud platform using automated build processes deployed using Infrastructure as Code
Provide technical challenge and assurance throughout development and delivery of work
Develop re-useable common solutions and patterns to reduce development lead times, improve commonality and lowering Total Cost of Ownership
Work independently and/or within a team using a DevOps way of working

What we offer

Extensive social benefits
Flexible working hours
Competitive salary
Shared values
Equal opportunities
Work-life balance
Evolving career opportunities
Comprehensive suite of benefits that supports physical, financial and emotional wellbeing

Fulltime

Senior Data Engineer – Data Engineering & AI Platforms

We are looking for a highly skilled Senior Data Engineer (L2) who can design, bu...

Location

India , Chennai, Madurai, Coimbatore

Salary:

Not provided

OptiSol Business Solutions

Expiration Date

Until further notice

Requirements

Strong hands-on expertise in cloud ecosystems (Azure / AWS / GCP)
Excellent Python programming skills with data engineering libraries and frameworks
Advanced SQL capabilities including window functions, CTEs, and performance tuning
Solid understanding of distributed processing using Spark/PySpark
Experience designing and implementing scalable ETL/ELT workflows
Good understanding of data modeling concepts (dimensional, star, snowflake)
Familiarity with GenAI/LLM-based integration for data workflows
Experience working with Git, CI/CD, and Agile delivery frameworks
Strong communication skills for interacting with clients, stakeholders, and internal teams

Job Responsibility

Design, build, and maintain scalable ETL/ELT pipelines across cloud and big data platforms
Contribute to architectural discussions by translating business needs into data solutions spanning ingestion, transformation, and consumption layers
Work closely with solutioning and pre-sales teams for technical evaluations and client-facing discussions
Lead squads of L0/L1 engineers—ensuring delivery quality, mentoring, and guiding career growth
Develop cloud-native data engineering solutions using Python, SQL, PySpark, and modern data frameworks
Ensure data reliability, performance, and maintainability across the pipeline lifecycle—from development to deployment
Support long-term ODC/T&M projects by demonstrating expertise during technical discussions and interviews
Integrate emerging GenAI tools where applicable to enhance data enrichment, automation, and transformations

What we offer

Opportunity to work at the intersection of Data Engineering, Cloud, and Generative AI
Hands-on exposure to modern data stacks and emerging AI technologies
Collaboration with experts across Data, AI/ML, and cloud practices
Access to structured learning, certifications, and leadership mentoring
Competitive compensation with fast-track career growth and visibility

Fulltime

Data Engineering & Analytics Lead

Premium Health is seeking a highly skilled, hands-on Data Engineering & Analytic...

Location

United States , Brooklyn

Salary:

Not provided

Premium Health

Expiration Date

Until further notice

Requirements

Bachelor's degree in Computer Science, Engineering, or a related field. Master's degree preferred
Proven track record and progressively responsible experience in data engineering, data architecture, or related technical roles
healthcare experience preferred
Strong knowledge of data engineering principles, data integration, ETL processes, and semantic mapping techniques and best practices
Experience implementing data quality management processes, data governance frameworks, cataloging, and master data management concepts
Familiarity with healthcare data standards (e.g., HL7, FHIR, etc), health information management principles, and regulatory requirements (e.g., HIPAA)
Understanding of healthcare data, including clinical, operational, and financial data models, preferred
Advanced proficiency in SQL, data modeling, database design, optimization, and performance tuning
Experience designing and integrating data from disparate systems into harmonized data models or semantic layers
Hands-on experience with modern cloud-based data platforms (e.g Azure, AWS, GCP)

Job Responsibility

Collaborate with the CDIO and Director of Technology to define a clear data vision aligned with the organization's goals and execute the enterprise data roadmap
Serve as a thought leader for data engineering and analytics, guiding the evolution of our data ecosystem and championing data-driven decision-making across the organization
Build and mentor a small data team, providing technical direction and performance feedback, fostering best practices and continuous learning, while remaining a hands-on implementor
Define and implement best practices, standards, and processes for data engineering, analytics, and data management across the organization
Design, implement, and maintain a scalable, reliable, and high-performing modern data infrastructure, aligned with the organizational needs and industry best practices
Architect and maintain data lake/lakehouse, warehouse, and related platform components to support analytics, reporting, and operational use cases
Establish and enforce data architecture standards, governance models, naming conventions ,and documentation
Develop, optimize, and maintain scalable ETL/ELT pipelines and data workflows to collect, transform, normalize, and integrate data from diverse systems
Implement robust data quality processes, validation, monitoring, and error-handling frameworks
Ensure data is accurate, timely, secure, and ready for self-service analytics and downstream applications

What we offer

Paid Time Off, Medical, Dental and Vision plans, Retirement plans
Public Service Loan Forgiveness (PSLF)

Fulltime

Data Engineer

As a Data Engineer at Rearc, you'll contribute to the technical excellence of ou...

Location

India , Bengaluru

Salary:

Not provided

Rearc

Expiration Date

Until further notice

Requirements

2+ years of experience in data engineering, data architecture, or related fields
Solid track record of contributing to complex data engineering projects
Hands-on experience with ETL processes, data warehousing, and data modelling tools
Good understanding of data integration tools and best practices
Familiarity with cloud-based data services and technologies (e.g., AWS Redshift, Azure Synapse Analytics, Google BigQuery)
Strong analytical skills
Proficiency in implementing and optimizing data pipelines using modern tools and frameworks
Strong communication and interpersonal skills

Job Responsibility

Collaborate with Colleagues to understand customers' data requirements and challenges
Apply DataOps Principles to create scalable and efficient data pipelines and architectures
Support Data Engineering Projects
Promote Knowledge Sharing through technical blogs and articles

Platform Engineer - Cloud

Join us as a Platform Engineer - Cloud at Barclays, responsible for supporting t...

Location

India , Pune

Salary:

Not provided

Barclays

Expiration Date

Until further notice

Requirements

Expert understanding of data lake and warehouse
Broad knowledge of public cloud services
Good understanding of data governance methodologies
Strong written and verbal communication skills demonstrating a collaborative approach across a range of stakeholders, including senior colleagues
Proven team player, supporting colleagues to achieve team objectives
Critical thinking

Job Responsibility

Build and maintenance of data architectures pipelines that enable the transfer and processing of durable, complete and consistent data
Design and implementation of data warehoused and data lakes that manage the appropriate data volumes and velocity and adhere to the required security measures
Development of processing and analysis algorithms fit for the intended data complexity and volumes
Collaboration with data scientist to build and deploy machine learning models

What we offer

Competitive holiday allowance
Life assurance
Private medical care
Pension contribution

Fulltime

Senior Data Engineering Architect

Location

Poland

Salary:

Not provided

Lingaro

Expiration Date

Until further notice

Requirements

Proven work experience as a Data Engineering Architect or a similar role and strong experience in in the Data & Analytics area
Strong understanding of data engineering concepts, including data modeling, ETL processes, data pipelines, and data governance
Expertise in designing and implementing scalable and efficient data processing frameworks
In-depth knowledge of various data technologies and tools, such as relational databases, NoSQL databases, data lakes, data warehouses, and big data frameworks (e.g., Hadoop, Spark)
Experience in selecting and integrating appropriate technologies to meet business requirements and long-term data strategy
Ability to work closely with stakeholders to understand business needs and translate them into data engineering solutions
Strong analytical and problem-solving skills, with the ability to identify and address complex data engineering challenges
Proficiency in Python, PySpark, SQL
Familiarity with cloud platforms and services, such as AWS, GCP, or Azure, and experience in designing and implementing data solutions in a cloud environment
Knowledge of data governance principles and best practices, including data privacy and security regulations

Job Responsibility

Collaborate with stakeholders to understand business requirements and translate them into data engineering solutions
Design and oversee the overall data architecture and infrastructure, ensuring scalability, performance, security, maintainability, and adherence to industry best practices
Define data models and data schemas to meet business needs, considering factors such as data volume, velocity, variety, and veracity
Select and integrate appropriate data technologies and tools, such as databases, data lakes, data warehouses, and big data frameworks, to support data processing and analysis
Create scalable and efficient data processing frameworks, including ETL (Extract, Transform, Load) processes, data pipelines, and data integration solutions
Ensure that data engineering solutions align with the organization's long-term data strategy and goals
Evaluate and recommend data governance strategies and practices, including data privacy, security, and compliance measures
Collaborate with data scientists, analysts, and other stakeholders to define data requirements and enable effective data analysis and reporting
Provide technical guidance and expertise to data engineering teams, promoting best practices and ensuring high-quality deliverables. Support to team throughout the implementation process, answering questions and addressing issues as they arise
Oversee the implementation of the solution, ensuring that it is implemented according to the design documents and technical specifications

What we offer

Stable employment. On the market since 2008, 1500+ talents currently on board in 7 global sites
Workation. Enjoy working from inspiring locations in line with our workation policy
Great Place to Work® certified employer
Flexibility regarding working hours and your preferred form of contract
Comprehensive online onboarding program with a “Buddy” from day 1
Cooperation with top-tier engineers and experts
Unlimited access to the Udemy learning platform from day 1
Certificate training programs. Lingarians earn 500+ technology certificates yearly
Upskilling support. Capability development programs, Competency Centers, knowledge sharing sessions, community webinars, 110+ training opportunities yearly
Grow as we grow as a company. 76% of our managers are internal promotions

Principal Data Engineer

We are on the lookout for a Principal Data Engineer to help define and lead the ...

Location

United Kingdom

Salary:

Not provided

Dotdigital

Expiration Date

Until further notice

Requirements

Extensive experience delivering python-based projects in the data engineering space
Extensive experience working with SQL and NoSQL database technologies (e.g. SQL Server, MongoDB & Cassandra)
Proven experience with modern data warehousing and large-scale data processing tools (e.g. Snowflake, DBT, BiqQuery, Clickhouse)
Hands on experience with data orchestration tools like Airflow, Dagster or Prefect
Experience using cloud environments (e.g. Azure, AWS, GCP) to process, store and surface large scale data
Experience using Kafka or similar event-based architectures e.g. (Pub/Sub via AWS SQS, Azure EventHubs, AWS Kinesis)
Strong grasp of data architecture and data modelling principles for both OLAP and OLTP workloads
Capable in the wider software development lifecycle in terms of agile ways of working and continuous integration/deployment of data solutions
Experience as a lead or Principal Engineer on large-scale data initiative or product builds
Demonstrated ability to architect data systems and data structures for high volume, high throughput systems

Job Responsibility

Lead the design and implementation of scalable, secure and resilient data systems across streaming, batch and real-time use cases
Architect data pipelines, model and storage solutions that power analytical and product use cases
using primarily Python and SQL via orchestration tooling that run workloads in the cloud
Leverage AI to automate both data processing and engineering processes
Assure and drive best practices relating to data infrastructure, governance, security and observability
Work with technologists across multiple teams to deliver coherent features and data outcomes
Support the data team to help adopt data engineering principles
Identify, validate and promote new tools and technologies that improve the performance and stability of data services

What we offer

Parental leave
Medical benefits
Paid sick leave
Dotdigital day
Share reward
Wellbeing reward
Wellbeing Days
Loyalty reward

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

Cloud Engineer, Data Processing

Aptiv plc

Location:
Mexico , Monterrey

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

Job Description:

Job Responsibility:

Requirements:

Nice to have:

Additional Information:

Job Posted:
February 20, 2026

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