AI/ML & Data Engineer Job at Congruent (Chennai)

Data Engineer - AI/ML

Data sits at the heart of the company. This role ensures that Awin can fully lev...

Location

Romania , Iași

Salary:

Not provided

Awin Global

Expiration Date

Until further notice

Requirements

Bachelor's degree or higher in Data Science, Data Engineering or a related field, preferably with a strong focus on mathematics, statistics, or data engineering
2+ years experience as data engineer on AI/ML project with Python
Strong experience using Databricks, including Jobs, Asset Bundles, Delta Lake, and MLflow, as well as Azure data engineering tools such as Azure Data Factory and Azure Data Lake Storage (ADLS)
Solid understanding of Scrum practices and a strong Agile mindset
Advanced proficiency in Python and its key data and ML libraries (NumPy, PySpark, Scikit learn, TensorFlow/PyTorch)
Working knowledge of generative AI models (e.g., ChatGPT, Claude), Databricks GenAI tooling (including embedding models), and modern data structures such as vector databases
Strong expertise in designing end to end ETL solutions using Databricks, including identifying, extracting, and curating datasets for machine learning model development
Strong knowledge of cloud platforms (Azure and AWS) and relevant services
Hands on experience with big data technologies, including Databricks and Spark
Very strong analytical skills to translate business need into actions with proactive approach to task and challenges, delivering project on time and budget

Job Responsibility

Write clean, elegant and maintainable code with Data engineering and AI/ML best practices
Understanding business objectives and developing models that help to achieve them, along with the creation and monitoring of business relevant metrics
Find new ways solve complex business problems with self improving automated predictive models
Evaluate existing models and recommend improvements for better result and performance efficiency
Develop best practices for building and orchestrating predictive models
Be responsible for quality, accuracy and interpretation of the result sets

What we offer

Flexi-Week and Work-Life Balance: a flexible four-day Flexi-Week at full pay and with no reduction to annual holiday allowance
Remote Working Allowance: a monthly allowance to cover part of your running costs
Flexi-Office: international culture and flexibility through Flexi-Office and hybrid/remote work possibilities to work across Awin regions
Meal Vouchers: a certain net sum to spend on a variety of lunches
Health & Wellbeing: insurance covering several types of health, vision and/or dental treatments for you and for up to one additional family member
Remote Working Furniture Package: after 3 months of employment, eligible for a furniture package to set up a proper workplace at your remote working location
Appreciation: thank and reward colleagues by sending them a voucher through our peer-to-peer program

Fulltime

Lead Data Engineer - AI/ML

The Lead Data Engineer will be part of a team building Stanford Health Care's (S...

Location

United States of America , Palo Alto

Salary:

94.35 - 125.03 USD / Hour

Stanford Health Care

Expiration Date

Until further notice

Requirements

Bachelor’s or Master’s degree in Computer Science, Engineering, or related, or equivalent working experience
5+ years experience in building data infrastructure for analytics teams, including ability to write code in SQL, R, or Python for processing large datasets in distributed cloud environments
Experience with cloud deployment strategies and CI/CD
Experience building and working with data infrastructure in a SaaS environment
Experience overseeing, developing or implementing machine learning operations (MLOps) processes
Experience mentoring junior engineers and enforcing best practices around code quality
Knowledge of multiple programming languages, commitment to choosing languages based on project-specific requirements, and willingness to learn new programming languages as necessary
Knowledge of resource management and automation approaches such as workflow runners
Collaborative mentality and excitement for iterative design working closely with the Data Science team.

Job Responsibility

Build end-to-end data pipelines and infrastructure for ML models used by the Data Science team and others at SHC
Understand the requirements of data processing and analysis pipelines and make appropriate technical design and interface decisions
Understand data flows among the SHC applications and use this knowledge to make recommendations and design decisions for languages, tools, and platforms used in software and data projects
Troubleshoot and debug environment and infrastructure problems found in production and non-production environments for projects by the Data Science Team
Work with other groups at SHC and the Technology and Digital Solutions (TDS) group to ensure servers and system maintenance based on updates, system requirements, data usage, and security requirements.

Fulltime

Senior Data & AI/ML Engineer - GCP Specialization Lead

We are on a bold mission to create the best software services offering in the wo...

Location

United States , Menlo Park

Salary:

Not provided

techjays

Expiration Date

Until further notice

Requirements

GCP Services: BigQuery, Dataflow, Pub/Sub, Vertex AI
ML Engineering: End-to-end ML pipelines using Vertex AI / Kubeflow
Programming: Python & SQL
MLOps: CI/CD for ML, Model deployment & monitoring
Infrastructure-as-Code: Terraform
Data Engineering: ETL/ELT, real-time & batch pipelines
AI/ML Tools: TensorFlow, scikit-learn, XGBoost
Min Experience: 10+ Years

Job Responsibility

Design and implement data architectures for real-time and batch pipelines, leveraging GCP services such as BigQuery, Dataflow, Dataproc, Pub/Sub, Vertex AI, and Cloud Storage
Lead the development of ML pipelines, from feature engineering to model training and deployment using Vertex AI, AI Platform, and Kubeflow Pipelines
Collaborate with data scientists to operationalize ML models and support MLOps practices using Cloud Functions, CI/CD, and Model Registry
Define and implement data governance, lineage, monitoring, and quality frameworks
Build and document GCP-native solutions and architectures that can be used for case studies and specialization submissions
Lead client-facing PoCs or MVPs to showcase AI/ML capabilities using GCP
Contribute to building repeatable solution accelerators in Data & AI/ML
Work with the leadership team to align with Google Cloud Partner Program metrics
Mentor engineers and data scientists toward achieving GCP certifications, especially in Data Engineering and Machine Learning
Organize and lead internal GCP AI/ML enablement sessions

What we offer

Best in class packages
Paid holidays and flexible paid time away
Casual dress code & flexible working environment
Medical Insurance covering self & family up to 4 lakhs per person

Software Engineer - Data Scientist AI/ML

Hewlett Packard Enterprise is the global edge-to-cloud company advancing the way...

Location

India , Bangalore

Salary:

Not provided

Hewlett Packard Enterprise

Expiration Date

Until further notice

Requirements

BS/MS in Computer Science or Data Science, Electrical Engineering, Statistics, Applied Math or equivalent fields with strong mathematical background
General understanding of machine learning techniques and algorithms, including clustering, anomaly detection, optimization, Neural network, Graph ML, etc
Experience building data science-driven solutions including data collection, feature selection, model training, post-deployment validation
Strong hands-on coding skills (preferably in Python) processing large-scale data set and developing machine learning models
Familiar with one or more machine learning or statistical modeling tools such as Numpy, ScikitLearn, MLlib, Tensorflow
Works well in a team setting and is self-driven

Job Responsibility

Collaborate with team to understand feature, work with domain experts to identify relevant “signals” during feature engineering, deliver generic and performant ML solutions
Keep up to date with newest technology trends
Communicate results and ideas to key decision makers
Implement new statistical or other mathematical methodologies as needed for specific models or analysis
Optimize joint development efforts through appropriate database use and project design

What we offer

Health & Wellbeing
Personal & Professional Development
Unconditional Inclusion

Fulltime

Data Engineer Lead (OT Data)

Data Engineer (OT Data) (Category - Engineer) Sector: Oil and Gas Location: Doha...

Location

Qatar , Doha

Salary:

Not provided

Codvo AI

Expiration Date

Until further notice

Requirements

Bachelor's in engineering, Information Systems, or a related quantitative field
5+ years of proven experience in a data engineering role
Experience within oil and gas industry is highly preferred
Demonstrable experience building and operationalizing large-scale data pipelines and applications

Job Responsibility

Architect & Build Data Pipelines: Design, construct, install, test, and maintain highly scalable data management systems and ETL/ELT pipelines
Integrate Diverse Data Sources: Develop processes to ingest and integrate high-volume, high-velocity data from SCADA systems, historians (like OSIsoft PI, Aspen InfoPlus.21), DCS, PLC, and IoT sensors
Cloud Data Platform Development: Implement and manage data solutions on the Microsoft Azure cloud platform, Leveraging services like Azure IoT Hub, Azure Event Hubs, and Azure Stream Analytics for real-time ingestion and processing of operational technology (OT) data
Data Modelling & Warehousing: Design and implement data models optimized for time-series data from industrial assets, supporting operational dashboards and real-time analytics
Enable Advanced AI: Build the data infrastructure to support AI/ML models for predictive maintenance, operational anomaly detection, and process optimization using real-time OT data
Champion Master Data Management (MDM): Design and implement MDM strategies and solutions to create a single, authoritative source of truth for critical data domains such as wells, equipment, and assets, ensuring data consistency across the enterprise
Ensure Data Quality & Governance: Implement robust data quality checks, validation rules, and monitoring to ensure the accuracy, consistency, and reliability of our data. Adhere to and help shape our data governance policies
Embrace Industry Standards: Champion and implement industry-specific data standards and models, such as the OSDU™ Data Platform, to ensure interoperability and a unified data view across the upstream lifecycle
Collaborate & Innovate: Work closely with a cross-functional team of geoscientists, drilling engineers, data scientists, and business analysts to understand their data needs and deliver effective solutions
Automate & Optimize: Identify opportunities for process automation and infrastructure optimization to improve data delivery, scalability, and cost-effectiveness

Fulltime

Solution Data Engineer – DG Infomatica Engineer

We are seeking a hands-on Informatica Developer with strong experience in data q...

Location

United States of America , TEMPE

Salary:

Not provided

Circle K

Expiration Date

Until further notice

Requirements

3–5+ years of hands-on experience as an Informatica Developer or Data Quality Engineer
Strong experience with Informatica IDMC, including: Cloud Data Quality (CDQ)
Cloud Data Catalog (EDC/CDGC)
Experience implementing data quality validation rules, monitoring, and reporting
Hands-on experience with Snowflake and Databricks
Experience working in Azure cloud environments (AWS exposure is a plus)
Strong SQL skills and understanding of data warehousing and data modeling concepts
Experience working with on-prem and cloud data sources
Experience configuring Informatica Secure Agents and cloud connectivity
Familiarity with REST APIs and system integrations

Job Responsibility

Design, develop, and maintain data quality rules, scorecards, and dashboards using Informatica CDQ
Implement and support metadata ingestion, cataloging, and lineage using Informatica Cloud Data Catalog (EDC/CDGC)
Onboard application and data source metadata in collaboration with application owners and data engineering teams
Configure and maintain technical and business assets, custom attributes, and custom lineage within the Informatica catalog
Extract and publish metadata from cloud and on-prem data sources to support enterprise metadata management
Support data lineage and impact analysis across Snowflake, Databricks, and relational databases
Configure and manage Informatica Cloud environments, including Secure Agents and connectivity
Integrate Informatica with cloud platforms and external systems using REST APIs
Partner with data engineering and analytics teams to ensure high-quality, well-governed datasets are available for reporting and AI/ML use cases

Data Engineer

Wells Fargo is seeking a Data Engineer to design, build and optimize scalable da...

Location

India , BENGALURU

Salary:

Not provided

Wells Fargo

Expiration Date

Until further notice

Requirements

2+ years of Data Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
Strong experience in EDL pipelines using Spark & BigQuery on GCP
Hands-on expertise in GCP services (BigQuery, Dataflow, GCS, IAM) and cloud-native architecture
Solid understanding of enterprise data governance, data quality
Exposure to AI/ML or GenAI use cases, including integration with data platforms and awareness of AI governance standards

Job Responsibility

Participate in data warehouses across multiple databases and identify opportunity for developing table schemas within the Technology and Date area
Review and analyze basic data management business, operational, or technical assignments or challenges that require research, evaluation, and selection of alternatives and exercise independent judgment to guide medium risk deliverables
Present recommendations for resolving more complex data management situations and exercise independent judgment while developing expertise in the business data policies, procedures and compliance requirements
Collaborate and consult with technology colleagues, internal partners and stakeholders, including internal and external customers if applicable
Design and build scalable, production-grade data pipelines on GCP supporting analytics and AI workloads
Develop and manage secure, compliant cloud data platforms aligned with enterprise policies and controls
Optimize data processing for performance, cost efficiency, and reliability (Spark + BigQuery workloads)
Collaborate with AI/analytics teams to enable feature engineering, model consumption, and AI-driven insights

Fulltime

New

Data Engineer – Lead

Location

India , Bengaluru Urban

Salary:

Not provided

NTT DATA

Expiration Date

Until further notice

Requirements

Strong hands-on experience with Microsoft Fabric, including Lakehouse, Warehouse, OneLake, Pipelines, Dataflows Gen2, Notebooks, and Power BI integration
Expertise in ETL/ELT, data pipelines, distributed data processing, and cloud-scale data engineering
Strong SQL, Python, PySpark, and data modeling skills
Experience with Lakehouse, Warehouse, and Medallion Architecture
Understanding of Delta tables, dimensional modeling, star schema, facts, dimensions, and curated analytical datasets
Experience integrating structured, semi-structured, file-based, API-based, enterprise application, and cloud data sources
Experience with data quality, reconciliation, logging, monitoring, and error-handling frameworks
Experience leading technical teams and coordinating onshore/offshore delivery
Experience with Git, CI/CD, Azure DevOps, branching, code reviews, and release management
Good to Have: Experience with Azure Data Factory, Synapse, Databricks, ADLS Gen2, Azure SQL, Microsoft Purview, or related Azure services

Job Responsibility

Lead the design and implementation of scalable data pipelines and data processing frameworks in Microsoft Fabric
Define data engineering standards, development practices, naming conventions, coding guidelines, and reusable technical patterns
Lead implementation of Bronze, Silver, and Gold layers in the Medallion Architecture
Oversee ingestion, transformation, orchestration, validation, and publication of data from multiple enterprise, clinical, operational, and cloud-based sources
Guide development of Fabric Pipelines, Dataflows Gen2, Notebooks, Lakehouse tables, Warehouse objects, and curated datasets
Ensure scalability, performance, reliability, maintainability, security, monitoring, and optimization of data solutions
Define standards for data quality, reconciliation, logging, error handling, auditability, and lineage
Conduct technical design reviews, code reviews, performance reviews, and deployment readiness reviews
Mentor and guide data engineering teams across onshore/offshore locations
Collaborate with architects, platform engineers, BI teams, QA teams, AI/ML teams, functional consultants, and stakeholders

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