Description

Design and optimize data infrastructure, pipeline architecture, and data flow for cross-functional teams.

Responsibilities

• Lead implementation of AWS data solutions based on volume, latency, security, and governance requirements.
• Manage large data projects and teams across multiple client engagements throughout the implementation lifecycle.
• Support presales and client problem definition phases by designing scoped data solutions.
• Provide hands-on guidance, mentoring, and validation for project teams during implementation.
• Identify and implement process improvements, including automating manual tasks and re-designing infrastructure for scalability.

Required Skills

• 10+ years of advanced SQL knowledge and experience with relational databases and query authoring.
• Extensive experience with the AWS Data Analytics stack, specifically EMR, Redshift, Kinesis/managed Kafka, and Glue.
• Proven experience handling streaming and time-series data using AWS Kinesis or AWS managed Kafka.
• Hands-on ETL development experience using SQL, Python, and Java/Scala.
• Experience implementing self-service data layers using data mesh, data fabric, or similar architectures.
• Familiarity with Lakehouse architectures and platforms such as Databricks.
• Ability to manage multiple client engagements simultaneously.
• Strong verbal and written communication skills for interacting with technical and executive stakeholders.

Preferred Skills

• Working experience with Snowflake or Databricks.
• Experience with Azure or GCP data stacks.
• Experience with dashboarding solutions like Tableau or Qlik.

Key Skills

Education

ANY GRADUATE