Description

Design and implement Azure data solutions while managing the full engagement lifecycle.

Assist in presales and client problem definition phases for Azure data engagements.

Design Azure data solutions and scopes that satisfy specific client requirements.

Manage multiple client engagements across different implementation lifecycle stages.

Provide hands-on guidance, mentoring, and validation for project teams during implementation.

Identify and implement internal process improvements, including automation and infrastructure redesign for scalability.

Required Skills

• 10+ years of experience in Data Engineering.
• 10+ years of advanced SQL knowledge, query authoring, and experience with relational databases.
• 5+ years of experience with the AWS Data Analytics stack, including EMR, Redshift, and Kinesis/managed Kafka.
• Hands-on experience handling streaming and time-series data using AWS Kinesis or AWS-managed Kafka.
• ETL development experience using SQL, Python, and Java/Scala.
• Experience implementing self-service data layers using data mesh, data fabric, or similar architectures for governance and sharing.
• Familiarity with Lakehouse architectures.
• Bachelor's degree or equivalent experience.

Preferred Skills

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

Key Skills

Education

Bachelor's degree