Design and develop data integrations to deliver Enterprise BI Data Marts and BI Semantic Data Layer(s)
Develop modern data engineering pipelines leveraging AI assisted capabilities, such as Databricks GenAI features and developer productivity tools (e.g., GitHub Copilot)
Lead multiple projects, provide technical guidance, and support other team members within the DAS organization
Improve data processes, technology infrastructure, and reporting and analytical services

Bachelor’s degree and 7 years of experience or 11 years of equivalent experience with data integration platforms
Strong technical experience in Business Intelligence Architecture and technologies
Experience working with a data architecture team to develop/manage a universal semantic model
Ability to work with business stakeholders to design, develop data products solution to enable insights
3 + years of experience working with Hadoop tech stack like HDFS, Hive, HQL, Spark, Scala, Pyspark/python, Sqoop
5 + years of experience working with SQL and Analytics
2 + years of experience working with MPP platforms like Teradata BTEQ, SQL etc
2 + years of experience working with Azure Cloud Analytics Services Synapse, ADLS, ADF, Azure SQL etc
Knowledge of DevOps / continuous deployment / integration process and tools
Knowledge of working with Enterprise grade scheduling tools like control M, Zena etc
Be an avid learner, gain a solid understanding of available data and promote innovative insights
Strong analytical skills
Written, communications and presentation skills, ability to source interpret and present analytics in a thoughtful and meaningful manner
Proactive self-starter, quick-learner, flexible team-player, ability to work both independently and as part of a team
Ability to multi-task, maintain strong attention to detail, and prioritize work within tight deadlines

Lead Analytics Engineer

Key skills