Description

You will lead the architecture and development of event-driven data warehouses, focusing on streaming, batch processing, and dimensional data modeling.

Responsibilities

• Partner with stakeholders to translate business requirements into technical specifications and process documentation.
• Design and develop ETL architectures including data profiling, process flow, metric logging, and error handling.
• Write and troubleshoot Python/PySpark scripts to cleanse, conform, and deliver data for consumption.
• Optimize SQL queries, stored procedures, functions, partitioning, and indexing via execution plan analysis.
• Lead junior engineers through code reviews and optimization training to improve solution quality and velocity.

Required Skills

• 10+ years of data development experience.
• Expertise in data warehouse design, dimensional modeling, and ETL process development.
• Proficiency in Python, PySpark, and Java.
• Advanced SQL/NoSQL scripting and complex stored procedure development.
• AWS expertise including Kinesis, Glue (Spark), EMR, S3, Lambda, and Athena.
• Experience with Confluent Kafka and Kinesis for streaming services.
• Hands-on experience designing applications using Java Spring Framework (Spring Boot, Spring Cloud, Spring Data).
• Proven experience working within an onsite-offshore delivery model.
• Bachelor's degree in Computer Science, MIS, or related field.

Preferred Skills

• Experience with Snowflake, SQL Server, DynamoDB, or Neo4j.

Key Skills

Education

Bachelor's degree in Computer Science