Lead Analytics Engineer

HCSC•Chicago, IL

About The Position

An individual with the ability to design and develop data integrations to deliver Enterprise BI Data Marts and BI Semantic Data Layer(s). This role requires strong technical skills across platforms such as RDBMS, MPP platforms (e.g., Teradata), Hadoop data lakes, Azure Cloud, and Azure Databricks, with the ability to design and develop end to end data integration and analytics engineering pipelines. The role includes developing modern data engineering pipelines leveraging AI assisted capabilities, such as Databricks GenAI features and developer productivity tools (e.g., GitHub Copilot), to accelerate design, development, and optimization of data solutions. As a Lead Analytics Engineer within the Enterprise Business Analytics & Business Intelligence team, this role is expected to lead multiple projects, provide technical guidance, and support other team members within the DAS organization. Many of these projects and initiatives are part of HCSC & DAS enterprise efforts to improve data processes, technology infrastructure, and reporting and analytical services.

Requirements

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
Proactive self-starter, quick-learner, flexible team-player, ability to work both independently and as part of a team

Nice To Haves

Strong experience with Databricks, including Spark-based data transformations and building scalable analytics pipelines
Hands-on expertise with Power BI, especially Semantic Model design, performance optimization, and enterprise reporting
Experience with Databricks GenAI features (GenAI Code, Databricks Agents) and Power BI Copilot to accelerate analytics development
Healthcare domain experience preferred, with the ability to work with healthcare data
Excellent analytical and problem‑solving skills, translating business needs into reliable, high‑quality data solutions

Responsibilities

Design and develop data integrations to deliver Enterprise BI Data Marts and BI Semantic Data Layer(s).
Design and develop end to end data integration and analytics engineering pipelines.
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.
Source, interpret, and present analytics in a thoughtful and meaningful manner.
Multi-task, maintain strong attention to detail, and prioritize work within tight deadlines.