Data Architect - ShellKode

Experience :

- 6+ years of experience in data engineering, data warehousing, or big data platforms.

- Proven experience in AWS cloud ecosystem (S3, Glue, EMR, Lambda, Redshift, Athena).

- Strong hands-on expertise with Apache Spark (Core, SQL, Streaming) and PySpark.

- Practical knowledge of Databricks for collaborative data engineering and ML workflows.

- Proficiency in Snowflake for data warehousing and analytics use cases.

- Strong programming skills in Python and SQL.

- Expertise in data modeling, ETL/ELT pipeline design, and data warehousing concepts.

- Experience with distributed and real-time processing frameworks like Flink

- Exposure to at least one BI tool (Tableau, Power BI, or QuickSight)

- Domain understanding in BFSI/ Fintech (preferred)

- Preferred experience in working with either Snowflake or Databricks

- Prior experience in designing and implementing at least 2+ large-scale production data migration or modernization projects

- Industry knowledge in Retail, Logistics, FSI, or Manufacturing would be an added advantage

Roles & Responsibilities :

- Design and architect scalable, secure, and performant big data solutions using AWS, Snowflake, or Databricks

- Strong understanding of performance tuning, cost optimization, and pipeline monitoring for reliable production workloads.

- Partner with business leaders, product managers, and clients to translate business objectives into technical data solutions

- Establish and enforce coding standards, architecture guidelines, and design patterns across projects

- Lead and mentor a team of data engineers and analysts, promoting best practices in data design and engineering

- Conduct code and architecture reviews, ensuring high-quality deliverables and adherence to technical standards.

- Collaborate with cross-functional teams to ensure seamless data delivery and alignment with business goals