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
Robust 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).
Robust 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