Description

You will lead the modernization of legacy data ingestion, ETL/ELT, and database systems to cloud platforms, ensuring scalable and secure architectures.

This role is on-site.

Responsibilities

• Modernize legacy data systems by migrating ingestion, ETL/ELT, and databases to AWS or Azure cloud technologies.
• Design and map ETL/ELT pipelines for new or modified data streams, integrating them into on-premise or cloud storage.
• Implement data access, classification, and security patterns that comply with regulatory standards including PII and locational data.
• Automate, validate, and maintain ETL/ELT processes using Databricks, ADF, SSIS, Spark, Python, and Scala.
• Conduct unit, system, and integration testing for ETL/ELT solutions and optimize pipeline performance.

Required Skills

• 4+ years of experience designing and implementing data warehouse and analytics solutions (on-premise and cloud).
• 3+ years of expertise in data warehousing concepts (ETL/ELT, data quality, privacy/security, MDM) with hands-on experience in ADF, Data Factory, and SSIS.
• 3+ years of experience with cloud data and cloud-native data lakes/warehouses, specifically Microsoft Azure services (Fabric Lakehouse, Synapse).
• 2+ years of experience in Python, Scala, or Java for distributed processing and analytics using Spark.
• Familiarity with CI/CD practices and tools such as Azure DevOps, Git, or Jenkins.
• Ability to perform data profiling and analysis on structured and unstructured data.
• Strong communication skills to collaborate with stakeholders, business analysts, and SMEs.

Preferred Skills

• Bachelor's degree in a related technical field.
• Experience working within a matrixed team environment sharing responsibilities across various teams.

Key Skills

Education

Bachelor's degree