Lead Data and Analytics Engineer
- Compensation
- Not disclosed
- Location
- North Chicago, IL, us
- Work setup
- Hybrid
- Seniority
- Lead
- Employment
- Not specified
- Experience
- 2+ years
- Category
- Data analytics
- Posted
Skills
Must have
- Bachelor's Degree with 7 years of experience; Master's Degree with 6 years of experience; or PhD with 2 years of relevant experience.
- Python and SQL proficiency required — expert-level ability to write production-quality code for pipeline automation, LLM enrichment, and enterprise integrations.
- Experience developing batch and real-time data pipelines using technologies such as Apache Spark, Apache Kafka, Apache Flink, Databricks, or equivalent platforms.
- Experience with modern cloud data platforms and services, such as Azure, AWS, or Google Cloud.
- Strong knowledge of data modeling, data warehousing, data lakes, and data lakehouse architectures.
- Experience implementing data quality, observability, lineage, metadata management, governance, and security.
- Familiarity with data orchestration tools like Apache Airflow, dbt, Prefect, etc.
- Experience preparing enterprise data for AI engineering use cases, including embedding and vectorization pipelines, Retrieval-augmented generation and semantic search architectures, Vector databases o
- Proven ability to deliver and maintain production-grade software in enterprise environments, including ongoing support, monitoring, and iterative improvements.
- Strong analytical, problem-solving, and diagnostic skills with ability to understand business processes and identify automation opportunities.
- Broad technical proficiency across software development, data integration, cloud platforms, and enterprise systems — with ability to rapidly learn and apply new technologies.
Nice to have
- Experience in the pharmaceutical industry or other highly regulated environments is preferred.
- Understanding of SDLC methodologies, GxP compliance, and validation requirements is preferred.
- Experience in working with international development teams across multiple time zones is preferred.
- Exposure to graph databases and GraphQL a plus.
Full description
As a Lead Data and Analytics Engineer, you will drive measurable business impact by designing and implementing data solutions that transform how our Corporate Services and HR business partners operate. You will serve as the critical bridge between complex business needs and technical execution—deeply understanding current-state processes, translating inefficiencies into innovative automation opportunities, and leveraging enterprise tools to deliver rapid ROI. This role uniquely combines hands-on technical leadership with strategic thinking: you will architect end-to-end solutions, build working prototypes, mentor the team in design thinking and agentic development, and ensure every solution drives tangible efficiency gains and value for stakeholders.
This role reports to the Associate Director, BTS Corporate Services within the Business Technology Solutions department. We set the vision for how data, analytics and AI automation enhance our enterprise systems. We work closely with business partners and technical implementors to bring that vision to life. This is a hybrid role required to be on-site Tuesday through Thursday every week in Lake County, IL.
Responsibilities:
- Engage deeply with Corporate Services and HR stakeholders to understand current-state processes, pain points, constraints, to-be business requirements, and success metrics; translate these into technical solution designs that deliver measurable efficiency gains.
- Engineer and implement scalable data engineering solutions; delivering clean, scalable, production-ready code that integrates with enterprise systems and optimizes business partner workflows.
- Prioritize rapid prototyping and iterative development, building working MVPs quickly to validate solutions with stakeholders, then refining based on feedback to accelerate time-to-value.
- Cultivate cross-team relationships while continuously expanding technical knowledge; identifying existing capabilities, shared platforms, and collaborative opportunities that maximize internal resources and drive productivity gains.
Required:
- Bachelor's Degree with 7 years of experience; Master's Degree with 6 years of experience; or PhD with 2 years of relevant experience.
- Python and SQL proficiency required — expert-level ability to write production-quality code for pipeline automation, LLM enrichment, and enterprise integrations.
- Experience developing batch and real-time data pipelines using technologies such as Apache Spark, Apache Kafka, Apache Flink, Databricks, or equivalent platforms.
- Experience with modern cloud data platforms and services, such as Azure, AWS, or Google Cloud.
- Strong knowledge of data modeling, data warehousing, data lakes, and data lakehouse architectures.
- Experience implementing data quality, observability, lineage, metadata management, governance, and security.