Lead Data and Analytics Engineer

Role Overview

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. 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.

What You Will Do

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.

Why It Might Be a Fit

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.

Requirements

• 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 or vector search capabilities, and generative AI and agentic AI applications.
• 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.
• Excellent written and oral communication skills, including ability to communicate technical concepts to non-technical stakeholders.
• Operate with high autonomy and minimal supervision—proactively managing stakeholder expectations and keeping leadership informed through clear, concise verbal and written communication.
• Demonstrated ability to mentor technical staff, lead cross-functional teams, and drive initiatives to completion.

Benefits

• Paid time off (vacation, holidays, sick)
• Medical/dental/vision insurance
• 401(k)
• Long-term incentive programs