Description

You will design and implement Azure data solutions while supporting the full engagement lifecycle.

Responsibilities

• 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.
• Strong verbal and written communication skills for interacting with technical and executive stakeholders.
• 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