Source description
About the role
Job Title: Data Engineer
Location: (Offshote) remote should be located in India
Contract Duration: 6 months
RATE: $22-$24/hour in C2C
Key Responsibilities:
- Data Pipeline Design & Development
Data Engineers are responsible for designing and building robust, scalable, and high-quality data pipelines that support analytics and reporting needs. This includes:
Integration of structured and unstructured data from various sources into data lakes and warehouses.
Build and maintain scalable ETL/ELT pipelines for batch and streaming data using Azure Data Factory, Databricks, Snowflake and Azure SQL Server, control -M.
Collaborate with data scientists, analysts, and platform engineers to enable analytics and ML use cases.
Design, develop, and optimise DBT models to support scalable data transformations.
- Cloud Platform Engineering
They operationalize data solutions on cloud platforms, integrating services like Azure, Snowflake, and third-party technologies.
Manage environments, performance tuning, and configuration for cloud-native data solutions.
- Data Modeling & Architecture
Apply dimensional modeling, star schemas, and data warehousing techniques to support business intelligence and machine learning workflows.
Collaborate with solution architects and analysts to ensure models meet business needs.
- Data Governance & Security
Ensure data integrity, privacy, and compliance through governance practices and secure schema design.
Implement data masking, access controls, and metadata management for sensitive datasets.
- Collaboration & Agile Delivery
Work closely with cross-functional teams including product owners, architects, and business stakeholders to translate requirements into technical solutions.
Participate in Agile ceremonies, sprint planning, and DevOps practices for continuous integration and deployment.
Key Skills Required
Programming: Python, SQL, Spark
Cloud Platforms: Azure, Snowflake
Data Tools: DBT, Erwin Data Modeler, Apache Airflow , API Integrations, ADF
Governance: Data masking, metadata management, SOX compliance
Soft Skills: Communication, problem-solving, stakeholder engagementTechnical Skills:
7+ years of data engineering or design experience, designing, developing, and deploying scalable enterprise data analytics solutions from source system through ingestion and reporting.
5+ years of experience in ML Lifecycle using Azure Kubernetes service, Azure Container Instance service, Azure Data Factory, Azure Monitor, Azure DataBricks building datasets, ML pipelines, experiments, logging, and monitoring. (Including Drifting, Model Adaptation and Data Collection).
5+ years of experience in data engineering using Snowflake.
Experience in designing, developing & scaling complex data & feature pipelines feeding ML models and evaluating their performance.
Experience in building and managing streaming and batch inferencing.
Proficiency in SQL and any one other programming language (e.g., R, Python, C++, Minitab, SAS, Matlab, VBA – knowledge of optimization engines such as CPLEX or Gurobi is a plus).
Strong experience with cloud platforms (AWS, Azure, etc.) and containerization technologies (Docker, Kubernetes).
Experience with CI/CD tools such as GitHub Actions, GitLab, Jenkins, or similar tools.
Familiarity with security best practices in DevOps and ML Ops.
Experience in developing and maintaining APIs (e.g.: REST)
Agile/Scrum operating experience using Azure DevOps.
Experience with MS Cloud - ML Azure Databricks, Data Factory, Synapse, among others.
More at 3B Staffing