
Senior Data Engineer
11 hours ago
We are seeking a Senior Data Engineer with strong hands-on expertise in designing and building modern data solutions. The ideal candidate will have deep technical skills across data engineering, cloud platforms, and AI frameworks, coupled with the ability to build end-to-end solutions and collaborate with solution architects, presales teams, and customers. Exposure to front-end development (dashboards, visualizations, or web apps) will be a strong advantage to deliver business-ready solutions.
Key Responsibilities Solution Build & DeliveryDesign, develop, and optimize data pipelines (ETL/ELT) using Azure Data Factory, Synapse, Databricks, and other modern tools.
Implement and maintain data lakes, warehouses, and real-time streaming platforms (Azure Synapse, Snowflake, SAAL.AI, Redshift, BigQuery).
Build AI/ML-enabled data solutions, integrating with Microsoft Fabric, Azure ML, and GenAI services.
Develop front-end components such as dashboards (Power BI, Streamlit, React/Angular) or lightweight web applications to enable data consumption.
Translate solution architecture into working prototypes and production-grade builds.
Collaborate with solution architects to ensure scalability, security, and performance in solution design.
Support PoCs, pilots, and innovation lab use cases.
Contribute to automation frameworks (e.g., n8n, Python scripts, CI/CD for data pipelines).
Key Responsibilities Customer & Practice SupportWork closely with customers, presales, and delivery teams to implement and optimize solutions.
Provide hands-on expertise in data migration, integration, and modernization projects.
Document best practices, reusable code templates, and accelerators for faster delivery.
Support Data & AI practice development through mentorship of junior engineers and active contribution to capability building.
Required Skills & ExperienceStrong hands-on skills in Microsoft Data Platform: Microsoft Fabric, Azure Synapse, Azure Data Lake, Azure SQL, Cosmos DB, Azure Data Factory, Azure Stream Analytics.
Experience with multi-platform data engineering: Snowflake, Databricks, SAAL.AI, AWS Redshift, BigQuery.
Proficiency in Python, PySpark, SQL, and automation frameworks (n8n, Airflow, etc.).
Solid understanding of data modeling, governance, and security best practices.
Familiarity with AI/ML and GenAI frameworks for embedding intelligence into solutions.
Exposure to front-end development (React, Angular, or dashboard frameworks like Power BI/Streamlit/Tableau).
Experience with CI/CD, Git, Docker, Kubernetes for modern DevOps practices.
Relevant certifications preferred: Microsoft Data Engineer Associate, Databricks Certified Data Engineer, Azure AI/ML certifications.
Preferred BackgroundExperience delivering projects in large Data projects.
Proven ability to work in cross-functional solution teams with architects, developers, and business stakeholders.
EducationBachelors or Masters degree in Computer Science, Data Science, Information Technology, or related field.
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