Sr Data Engineering Manager

McLane; Round Rock (TX); Hybrid; USD 150,000 - 210,000; Full time

Benefits offered by this job

Day 1 benefits (medical, dental,Vision

401(k) profit sharing

Paternity/maternity leave

Tuition reimbursement

Pet insurance

Job summary

McLane is seeking a Sr. Data Engineering Manager to lead data engineering strategy and modernize pipelines, with a focus on AI-enabled analytics and scalable data platforms. The role requires collaboration with stakeholders and leadership of cross-functional teams.

Hybrid work arrangement with on-site presence required; candidates should be within driving distance of Temple, TX. Strong expertise in SQL, Python, and cloud data services is expected.

Qualifications

• Bachelor's degree in Computer Science, Engineering, Statistics, or related field.

Responsibilities

• Define and execute the data engineering strategy and operating model.
• Lead the design, development, and modernization of scalable data engineering pipelines.
• Champion the application of AI across data engineering practices, platforms, and products.
• Lead cloud and hybrid platform modernization (lakehouse, streaming, real-time + batch ingestion).
• Establish enterprise standards & architectures (ELT/ETL, data modeling, semantic layer).
• Drive data governance (quality, lineage, security, access, SLAs).
• Deliver scalable, reliable, cost-optimized platforms (FinOps, performance).
• Build reusable data pipelines & domain data products enabling analytics and AI/ML.
• Partner with stakeholders to translate business needs into technical solutions.

Job description

Job Description

Take your career further with McLane! McLane teammates, the driving force behind our success, are diverse professionals who work together seamlessly to keep our operations running smoothly. As a teammate, you will pair your dedication, expertise, and collaborative spirit with your fellow teammates to serve America's most beloved brands. McLane leaders think long-term, act with purpose, and inspire high performance. They lead with accountability, communicate clearly, and drive results through collaboration, innovation, and continuous growth. They empower each teammate to learn from industry leaders, develop their skills, and build lasting connections nationwide.

We're looking for an enthusiastic and experienced Sr. Data Engineering Manager who is passionate about applying AI while building and evolving modern data engineering pipelines. This leader will combine strong technical expertise with seasoned people leadership and the ability to understand stakeholder requirements, communicate effectively across technical and business teams, and translate business needs into scalable data solutions. The role will help build an AI-ready data ecosystem that supports analytics, automation, and digital supply chain outcomes.

This is a hybrid position which will require the candidate to report and work from the office at least three days a week. Therefore, interested candidates should be within a 50-minute radius from Temple, TX.

Benefits you can count on:

Day 1 Benefits: medical, dental, and vision insurance, FSA/HSA, and company-paid life insurance Paid time off begins day one. 401(k) Profit Sharing Plan after 90 days. Additional benefits: pet insurance, maternity/paternity leave, employee assistance programs, discount programs, tuition reimbursement program, and more!

What You'll Do:

• Define and execute the data engineering strategy and operating model. (domain teams, platform teams, governance)
• Lead the design, development, and modernization of scalable data engineering pipelines.
• Champion the application of AI across data engineering practices, platforms, and products.
• Lead cloud and hybrid platform modernization. (lakehouse, streaming, real-time + batch ingestion, legacy migration)
• Establish enterprise standards & architectures. (ELT/ETL, medallion, semantic layer, data modeling, streaming)
• Drive data governance. (quality, lineage, security, access, SLAs, data contracts)
• Ensure compliance & audit readiness. (privacy-by-design, SOX, GDPR/CCPA alignment)
• Deliver scalable, reliable, cost-optimized platforms. (performance engineering, FinOps)
• Build reusable data pipelines & domain data products enabling analytics and AI/ML.
• Partner with stakeholders and business leaders to understand requirements, translate business needs into technical solutions, and communicate priorities, tradeoffs, and outcomes effectively.
• Implement DataOps practices. (CI/CD, testing, observability, incident response)
• Lead and develop high-performing teams. (hiring, coaching, succession planning)
• Manage vendor strategy, tooling, and technology selection.
• Drive continuous improvement through SLIs/SLOs, pipeline performance, data quality, and cost metrics.

What We're Looking For:

• Education: Bachelor's degree in Computer Science, Engineering, Statistics, or related field.
• Experience 7+ years in data engineering / data platform engineering, including 3+ years leading teams. (manager-of-managers preferred)
• Seasoned leader with demonstrated success managing technical teams, priorities, and stakeholder expectations.
• Strong enthusiasm for AI and demonstrated interest in applying AI to data engineering, automation, analytics, and business solutions.
• Strong stakeholder management and communication skills with the ability to translate technical concepts and requirements for both technical and non-technical audiences.
• Data Engineering in GCP is preferred.
• Cloud Composer (Airflow), Dataproc (Spark/PySpark), Dataflow, Dataform, BigQuery SQL transformations
• Datastream (CDC), Cloud Storage (GCS), Pub/Sub, Knowledge Catalog, Data Quality frameworks, Metadata & lineage
• Microsoft Fabric experience is a plus (Skillset listed below): Fabric Lakehouse, Fabric Notebooks (PySpark), Data Factory Pipelines, Dataflow Gen2, Spark SQL, Git / source control, REST APIs and JSON processing, Delta/Parquet file formats
• Strong expertise in Spark, batch + streaming pipelines, and modern data architectures.
• Advanced proficiency in SQL & Python.
• Proven experience with ELT/ETL, orchestration, data modeling (dimensional/Data Vault), and metadata/lineage.
• Expertise in DataOps & engineering excellence. (CI/CD, IaC, Git, monitoring, incident management)
• Solid understanding of data governance, security, and privacy controls. (IAM, encryption, retention, lineage)
• Experience translating business needs into technical solutions and driving cross-functional alignment.
• Background in vendor evaluation, budgeting, and tool selection.
• Strong communication skills with abilit