Senior Data Engineer Insurance

Key Responsibilities

• 4-6 years of relevant work experience.
• Design, store, process, and maintain large-scale data systems and related infrastructure.
• Drive multiple projects from both operational and technical standpoints.
• Ideate and build PoVs/PoCs for new products that can help drive more business.
• Define, design, and implement data engineering best practices, strategies, and solutions.
• Act as an architect guiding customers, the team, and the organization on tools, technologies, and best practices in data engineering.
• Lead architecture discussions and align them with business needs, security, and best practices.
• Demonstrate strong conceptual understanding of Data Warehousing, ETL, Data Governance, Security, Cloud Computing, and Batch & Real-Time Data Processing.
• Apply strong execution knowledge of Data Modeling, SQL/NoSQL databases, SDLC practices, unit testing, and functional programming.
• Understand and work with Medallion architecture patterns.
• Work on at least one major cloud platform.
• Execute multiple end-to-end data engineering projects as a data architect.
• Possess extensive knowledge of various data architecture designs and data modeling concepts.
• Manage conversations with client stakeholders, understand requirements, and translate them into technical outcomes.

Required Skills and Experience

• Strong proficiency in SQL.
• Experience working with any major cloud platform (AWS, Azure, or GCP).
• Working knowledge of ETL/orchestration tools (IICS, Talend, Matillion, Airflow, ADF, AWS Glue, GCP Composer, etc.).
• Working knowledge of OLTP databases (Postgres, MySQL, SQL Server, etc.).
• Working knowledge of Data Warehouses such as Snowflake, Redshift, Azure Synapse, Hive, BigQuery, etc.
• Proficiency in at least one data engineering programming language such as Python (or Scala/Rust/Java).
• Strong execution knowledge of Data Modeling (star schema, snowflake schema, fact/dimension tables).
• Proficient in Spark and related platforms (Databricks, GCP DataProc, AWS Glue, EMR, etc.).
• Experience working with Kafka and real-time streaming.
• Strong understanding of data architecture patterns (Lambda, Kappa, data harmonization, CDP patterns, etc.).
• Experience in code and SQL optimization.
• Strong knowledge of Git and CI/CD pipeline design for continuous delivery.
• Experience with data and networking security (RBAC, secret management, key vaults, VNets/subnets, certificates).