This is a hands on data platform engineering role that places significant emphasis on consultative data engineering engagements with a wide range of customer stakeholders; Business Owners, Business Analytics, Data Engineering teams, Application Development, End Users and Management teams.

Additional Information

7+ years of data engineering experience leading implementations of large-scale lakehouses on Databricks, Snowflake, or Synapse. Prior experience using DBT and PowerBI will be a plus.

3+ years' experience architecting solutions for developing data pipelines from structured, unstructured sources for batch and realtime workloads.

Extensive experience with Azure data services (Databricks, Synapse, ADF) and related azure infrastructure services like firewall, storage, key vault etc. is required.

Strong programming / scripting experience using SQL and python and Spark.

Strong Data Modeling, Data lakehouse concepts.

Knowledge of software configuration management environments and tools such as JIRA, Git, Jenkins, TFS, Shell, PowerShell, Bitbucket.

Experience with Agile development methods in data-oriented projects

Highly motivated self-starter and team player and demonstrated success in prior roles.

Track record of success working through technical challenges within enterprise organizations

Ability to prioritize deals, training, and initiatives through highly effective time management

Excellent problem solving, analytical, presentation, and whiteboarding skills

Track record of success dealing with ambiguity (internal and external) and working collaboratively with other departments and organizations to solve challenging problems

Strong knowledge of technology and industry trends that affect data analytics decisions for enterprise organizations

Certifications on Azure Data Engineering and related technologies.

Rackspace

Senior Data Engineer – Azure