Data Architect

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.

Key Skills:

• Technologies: AWS, Snowflake, Databricks, Spark, Python, SQL, Airflow, Kafka.

• Frameworks: Spark Core, Spark SQL, Spark Streaming/Flink.

• Soft Skills: Leadership, stakeholder management, Team Management, communication, problem-solving, decision-making.