Data Engineer (Databricks) - Contract

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Description

About the Role Our clientis looking for a Data Engineer with hands-on experience in Databricks and Snowflake to design, build, and maintain modern data pipelines and platforms. You will work closely with analysts, data scientists, and product teams to turn raw data into trusted, high-quality datasets that drive analytics, reporting, and machine learning. Key Responsibilities • Design, build, and optimize scalable batch and streaming data pipelines using Databricks (Spark, Delta Lake) and Snowflake. • Develop and maintain ELT/ETL workflows that ingest data from databases, APIs, event streams, and files. • Model data using dimensional and lakehouse approaches (e.g., medallion architecture) to support analytics and ML use cases. • Tune performance and manage cost across Databricks clusters and Snowflake warehouses. • Implement data quality checks, monitoring, alerting, and lineage to ensure reliability and trust in data. • Apply data governance and security best practices, including access control, masking, and compliance requirements. • Build CI/CD and infrastructure-as-code practices for data pipelines. • Collaborate with stakeholders to understand requirements and translate them into technical solutions. • Document pipelines and data models, and mentor junior engineers through code reviews and knowledge sharing. Required Qualifications • 3 to 7 years of professional experience in data engineering. • Strong hands-on experience with Databricks (Spark, PySpark/Spark SQL, Delta L

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