Data Architect (Databricks & Snowflake)

Role: Data Architect (Databricks & Snowflake) Location: Boston, MA - Hybrid (as needed) - The customer is seeking local candidates only (in and around Boston) to ensure the consultant can visit the office when required. Contract LOCAL Profile Only Ideally 15+ years experience required Digital : Snowflake Job Summary 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. \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_ Key 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. \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_ Required Qualifications • 10+ years (ideally 15–20+) of experience in data engineering or data architecture. • Strong expertise in: o Databricks & Delta Lake o Snowflake Data Warehouse o 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. \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_ Preferred Qualifications • 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. \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_ Key Skills • Data Engineering & Architecture • Lakehouse & Data Warehousing • Spark Performance Optimization • Cloud Data Platforms (Azure) • ETL/ELT Pipeline Development • Data Governance & Security • CI/CD & DevOps Practices \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_ Education • Bachelor’s degree in Information Technology, Computer Science, or a related field. \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_ Nice-to-Have Traits • 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