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 robust 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.
- Robust 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).

📌 Senior Data Engineer Insurance (Bengaluru)
🏢 MathCo India
📍 Bengaluru