Data Engineering Manager

BSF; Jacksonville (FL); On-site; USD 120,000 - 180,000; Full time

Job summary

BSF is seeking a Manager of Data Engineering in Jacksonville, FL. This hands-on leadership role combines working as a data engineer with managing a small engineering team to deliver the Unified Data Platform and MDM initiatives.

The role requires deep expertise in Azure Databricks, Python/SQL/Spark, and ERP data ingestion (NetSuite). You will partner with executives and operations to ensure reliable data for analytics and decision-making.

Qualifications

• 6+ years in data engineering with pipeline architecture and hands-on delivery.
• 2+ years leading or mentoring a technical team.
• Strong proficiency in Azure data services and Databricks.
• Proficiency in Python, SQL or Spark; hands-on coding capability.
• Experience delivering a data platform or MDM initiative in a multi-source environment.
• Working knowledge of NetSuite or similar ERP data ingestion.

Responsibilities

• Hands-on data engineering ~50% of the role, building data pipelines in Azure/Databricks.
• Lead and coach a two-person data engineering team, guiding priorities and growth.
• Drive the MDM initiative and overall UDP platform delivery with clear milestones.
• Establish and enforce engineering standards, documentation, testing and code reviews.
• Partner with business stakeholders to translate data needs into engineering work.

Skills

Data engineering

Team leadership

Azure Databricks

Python/SQL/Spark

NetSuite data ingestion

Git / CI/CD

MDM / data platform

ERP data familiarity

Tools

Git

CI/CD

Job description

The Manager of Data Engineering is the technical lead and people manager for BSF's Data Engineering function: the team responsible for building and maintaining the pipelines, architecture and infrastructure that power BSF's data platform. This is a hands-on role: roughly half of this role's time is spent as a working Data Engineer, in the code alongside the team, and half is spent leading, coaching and removing blockers for that team.

This role sits at the foundation of everything BSF's data function delivers in partnership with the Data Solutions Manager. Data isn't just an analytics input — it's the backbone of the company, running through everything from the warehouse floor to the executive dashboard. The Manager of Data Engineering is accountable for that foundation: the analytics team's trusted insights depend on it and so does every operational system built on the same data.

The Manager reports to the VP of Data & Analytics and operates as a key technical partner in delivering BSF's Unified Data Platform, including the Master Data Management initiative that is a top priority for the data function right now.

The Manager of Data Engineering brings the team, the delivery discipline and the hands-on build to ensure data.

TEAM SCOPE

The Manager leads a team of two Data Engineers and is accountable for their output, development and day-to-day direction. The Manager's job is to give them direction, remove blockers, raise the bar on engineering standards and ensure their work connects directly to what the business needs.

CORE RESPONSIBILITIES

Hands-On Data Engineering (~50% of role)

• Architect and build data pipelines that ingest, transform and deliver data from BSF's core systems including NetSuite, WMS and manufacturing platforms
• Contribute production-quality code directly in Python, SQL and Spark within the Azure/Databricks environment: this role is expected to be in the build alongside the team, not above it
• Own technical execution on a meaningful share of the data engineering backlog, not just review and delegate
• Participate in code reviews as both reviewer and contributor
• Stay current in the Azure and Databricks ecosystem: evaluate new capabilities and bring forward recommendations that improve the platform

Technical Leadership and Architecture

• Partner with the Data Solutions Manager and VP of Data & Analytics on the Data Engineering architecture for BSF's Unified Data Platform: bringing forward design recommendations that are scalable, maintainable and appropriate for BSF's stage of data maturity
• Lead the technical execution of the MDM initiative: a top priority for the data function right now
• Establish and enforce engineering standards including pipeline reliability, documentation, testing and code review practices

Team Leadership and Development

• Lead, coach and develop a team of data engineers
• Know each person's technical strengths, growth edges and what they need to do their best work
• Create an environment where technical questions are welcomed, knowledge is shared and no one person is a single point of failure
• Give feedback directly and in the moment: on code quality, technical decisions and professional growth
• Partner with the VP of Data & Analytics to assess team capability honestly and make recommendations about structure, capacity and development needs
• Own hiring, performance management and day-to-day people leadership for the data engineering team

MDM and Platform Delivery

• Lead and be accountable for the data engineering workstream of the MDM/UDP project: maintaining a clear delivery plan, tracking progress and surfacing risks early
• Ensure NetSuite data ingestion, BSF's most complex and critical data source, is complete, reliable and well-documented
• Drive the platform toward production deliverables with defined timelines, named owners and visible status
• Establish a shared definition of success with business stakeholders for every major platform initiative: not just technical completion, but business usability

Data Quality and Governance

• Be accountable for data quality at the pipeline level: what goes in wrong comes out wrong and this team is the first line of defense
• Build and maintain data documentation, data dictionaries and lineage tracking, in partnership with the Data Solutions Manager and Data Governance team, so the organization knows what it has and where it came from
• Partner with the Data Governance team and VP of Data & Analytics to establish and enforce data standards across source systems
• Proactively surface data quality issues to business stakeholders: don't wait to be asked

Cross-Functional Partnership

• Work closely with the Analytics team to ensure the data they need is available, reliable and structured for consumption: engineering and analytics succeed together or not at all
• Partner with the Data Solutions Manager on clean data handoffs from operational systems to the platform: clean handoffs, clear interfaces, no silent gaps
• Engage directly with business stakeholders in Operations, Finance and Supply Chain to understand their data needs and translate them into engineering requirements
• Represent the data engineering team's capacity and delivery commitments honestly: no overpromising, no silent underdelivering

WHAT YOU WILL BRING

• 6 or more years in data engineering, with demonstrated depth in pipeline architecture and hands-on production delivery
• 2 or more years leading or mentoring a technical team
• Strong proficiency in Azure data services: Databricks, Azure Data Factory, ADLS Gen2 and/or Lakehouse architecture
• Proficiency writing and reviewing production-quality code in Python, SQL or Spark: you can sit down and build, not just direct
• Experience delivering a data platform or MDM initiative in a complex, multi-source environment
• Working knowledge of NetSuite or similar ERP data structures and the challenges of ingesting customized ERP data
• Proficiency with source control (Git) and CI/CD practices
• Experience in food distribution, manufacturing or supply chain is a meaningful plus

HOW WE LEAD AT BSF

Leadership at BSF is not a title: it's a practice. We expect our leaders to know their people, develop them deliberately and hold themselves accountable for the growth of everyone on their team.

• You know every person on your team: their strengths, their growth edges, what motivates them and what's getting in their way. You can speak to each one without looking at notes.
• You give feedback directly and in the moment: not just in reviews, not softened into meaninglessness, and not saved up until it becomes a bigger conversation than it needs to be.
• You can tell the difference between someone who needs coaching, someone who's in the wrong seat and someone who's in the wrong organization. You act on that difference with clarity and care.
• You develop people by raising the bar, not by protecting them from it.
• You build teams that don't depend on you to function. Knowledge lives in the team, not in one person, including you.
• You model what you expect. If you want accountability, you're accountable. If you want transparency, you're transparent first.

WHAT THIS ROLE REQUIRES

• Deep hands-on experience in data engineering: you write code, review code and can architect a solution from first principles
• Comfort splitting your week between hands-on development and people leadership, without letting either one slide
• Strong proficiency in Azure data services and Databricks: this is BSF's platform and you need to be credible in it
• Proven ability to lead and develop a technical team: not just assign tickets, but grow people
• Strong data quality instincts: you care about what goes into the pipeline as much as what comes out
• Clear communicator who can translate technical complexity into business language, and business requirements into engineering scope
• A builder's mindset: you create structure, document what matters and leave the platform better than you found it
• Comfort operating in a high-growth, high-ambiguity environment where the roadmap is real but not everything is perfectly defined