Information Technology_USA - USA_Engineer
About The Position
We are seeking a highly experienced Senior Data Engineer / Data Architect with deep expertise in Databricks, Snowflake, and Azure cloud data platforms. The ideal candidate will have extensive experience designing and implementing scalable data pipelines, Lakehouse architectures, and real-time data processing solutions, particularly in regulated domains such as Life Sciences or Healthcare. This role requires strong proficiency in Spark (PySpark), Delta Lake, Medallion architecture, and cloud-native data engineering practices, along with a solid background in data warehouse modernization and performance optimization.
Requirements
- 10+ years (ideally 15–20+) of experience in data engineering or data architecture.
- Strong expertise in: Databricks & Delta Lake
- Snowflake Data Warehouse
- Apache Spark (PySpark, Spark SQL)
- Hands-on experience with Azure Cloud (ADLS Gen2, Azure Databricks, ADF).
- Proficiency in Python and SQL for data engineering.
- Experience with ETL/ELT tools such as Talend or Informatica.
- Strong knowledge of data modeling, CDC (Change Data Capture), and incremental loading techniques.
- Experience working in Linux/Unix environments with shell scripting.
Nice To Haves
- Knowledge of data governance, compliance, and regulatory standards (e.g., IDMP).
- Exposure to real-time data streaming technologies (Kafka, Kinesis).
- Experience with multi-cloud environments (AWS, GCP).
- Familiarity with workflow orchestration tools such as Airflow or Databricks Workflows.
- Strong analytical and problem-solving skills
- Ability to work in enterprise-scale, complex environments
- Experience working with global stakeholders and cross-functional teams
- Leadership capability with mentoring experience
Responsibilities
- Design and implement end-to-end data engineering pipelines using Azure Databricks, ADLS Gen2, and Snowflake.
- Develop scalable ETL/ELT pipelines using PySpark, Spark SQL, Python, and Talend.
- Build and maintain Lakehouse architecture using Delta Lake and Medallion (Bronze, Silver, Gold) layers.
- Implement real-time and batch data ingestion pipelines, including streaming using Spark Structured Streaming.
- Design and enforce data governance, access control, and lineage using Unity Catalog.
- Optimize Spark workloads through partitioning, caching, broadcast joins, and cluster tuning to improve performance and reduce cloud costs.
- Architect and manage CI/CD pipelines using Azure DevOps, Jenkins, and Git for automated deployments.
- Integrate multiple data sources and systems, ensuring high-quality, reliable, and scalable data delivery.
- Collaborate with cross-functional teams including data analysts, scientists, and business stakeholders to support analytics and reporting needs.
- Support data warehouse modernization initiatives, including migration from legacy systems to cloud platforms.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
