Mid Level Data Analytics Engineer Jobs
Mid level data analytics engineer jobs go to engineers ready to own data pipelines and reporting systems end to end, mentor junior teammates, and translate complex findings into decisions with limited oversight. Roles cover on-site, hybrid, and remote settings across Consulting & Professional Services, Investment & Asset Management, and Accounting & Auditing, with employers like Deloitte, Amazon, and Capital One hiring at this level now.
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Job Description
Company: Wells Enterprises (a Ferrero Company)
Functional Area: IT
The Role
Coordinate and execute the enterprise data governance program while enabling analytics and AI adoption across business teams. Partner with business stakeholders, data owners, analysts, and Information Technology teams to maintain governance artifacts, standardize data definitions, support data quality and ownership discussions, and translate business needs into actionable analytics and data modernization requirements. Apply strong knowledge of data structures, reporting data sources, BI tools, SQL, and data modeling concepts to support reliable self-service analytics, governance documentation, training, and change management activities.
What You’ll Do
- Manage day-to-day execution of the enterprise data governance program, including governance roadmap maintenance, action item tracking, stewardship meeting preparation, committee coordination, process artifact management, and follow-up on commitments.
- Work directly with business stakeholders to gather requirements, capture concerns, facilitate data ownership and definition discussions, and build cross-functional consensus around data governance and analytics needs.
- Maintain business glossaries, data definitions, governance documentation, data quality guidance, and related process artifacts so business and technical teams have consistent, current, and usable reference materials.
- Support analytics and AI enablement through adoption planning, communication planning, training coordination, user engagement activities, community building, and feedback loops that improve business understanding and self-service adoption.
- Collaborate with data analytics, Information Technology, architecture, and platform teams to support data modernization workstreams, BI source alignment, cloud data platform readiness, report refresh considerations, security awareness, and reliable analytics delivery.
- Mentor junior analysts and business users by reviewing presentations and deliverables, coaching communication and storytelling skills, providing business context, and supporting onboarding into governance, analytics, and AI enablement practices.
Qualifications
What You’ll Bring
- Bachelor’s degree in information technology, data analytics, business, information systems, engineering, or related field. Data governance, data management, analytics, or BI certification preferred.
- 5-7 years of experience in data analytics, BI, data governance, data management, or related business technology roles. Experience partnering with business stakeholders to gather requirements, define data needs, document processes, improve data quality, and support adoption of analytics or governance practices. Hands-on experience with Databricks, BI/reporting tools such as Tableau or related technologies, SQL, relational databases and data modeling concepts is preferred. Background in CPG, manufacturing, finance, supply chain, sales, or enterprise operations is a plus.
- Strong working knowledge of relational and reporting database structures, data modeling, data definitions, data quality concepts, business glossaries, metadata, and governance practices. Understands how data is sourced, transformed, modeled, secured, consumed, and refreshed for BI, reporting, analytics, and AI-enabled use cases. Familiarity with Databricks and BI tools such as Tableau or related technologies is preferred. Familiarity with SQL, Python or R, Oracle or related databases, Azure or cloud data storage, and modern analytics platforms is a plus.
- Skilled in translating business questions into clear data requirements, governance artifacts, definitions, and adoption plans. Strong communication, facilitation, documentation, training coordination, and stakeholder engagement skills. Able to gather datasets, understand reports and dashboards, validate business logic, support data source alignment, and review deliverables for clarity, usability, and business relevance. Able to collaborate and build trust across business partners, Information Technology, analysts, data stewards, and platform teams. Technologies used may include Databricks, Azure DevOps, and Microsoft 365 productivity tools.
- Able to thrive in a fast-paced and dynamic environment with limited supervision while maintaining strong follow-through, documentation discipline, and stakeholder responsiveness. Able to facilitate groups, guide constructive decision-making, challenge unclear business rules, identify risks or blockers, and recommend practical paths forward. Able to work comfortably with large datasets, reporting logic, data definitions, and analytics outputs while keeping the business user experience in focus. Able to coach others, support adoption, ask thoughtful questions, seek better outcomes, and help teams use data responsibly and consistently.
Compensation
The base pay range for this position is $87,321 to $139,061 annually. Actual compensation will be determined based on location, experience, skills, qualifications, and other job-related factors permitted by law. This pay range represents the anticipated salary for this position at this time.
Wells Enterprises is an EEO/AA employer M/F/Vet/Dis
About us
Wells Enterprises, a Ferrero company, is one of the largest ice cream manufacturers in the United States and the maker of well-loved brands including Blue Bunny, Halo Top, Bomb Pop, and Blue Ribbon Classics and today Trolli, Butterfinger 100grand, Baby Ruth, Nutella and Kinder Bueno. Wells Enterprises is a 2 billion company employing 4,000 employees, across 4 production plants and 2 main hub locations, Chicago and Le Mars. Guided by innovation, quality, and a people-first mindset, Wells is committed to delighting consumers and developing exceptional teams. As part of the Ferrero Group, Wells combines its strong U.S. heritage with Ferrero’s global standards of excellence, offering a unique opportunity to grow within a dynamic, values-driven, and international environment. At Wells, our people—and their experience—sit at the heart of our ambition.
What We Offer
At Wells, we’re proud to support our employees with comprehensive benefits that enhance health, financial wellness, and include paid time off (PTO). Eligible employees may also receive an annual incentive bonus based on Company performance.
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Find JobsMid Level Data Analytics Engineer Job Market
Who's Hiring
- Deloitte19

- Amazon4

- Capital One4

- 4P Consulting4

- JPMorganChase3

Top Industries Hiring
- Consulting & Professional Services28
- Investment & Asset Management20
- Accounting & Auditing19
- Technology & Software19
- Banking & Financial Services10
Mid Level Data Analytics Engineer Jobs: Frequently Asked Questions
How do I get a mid level data analytics engineer job?
Position yourself around ownership, not just contribution. Highlight projects where you defined the approach, resolved ambiguity, and delivered a result stakeholders acted on. Show proficiency in SQL, a cloud data platform, and at least one BI or transformation tool. Applications that demonstrate you can work independently and communicate findings to non-technical audiences stand out at this level.
Which companies hire mid level data analytics engineers?
Companies hiring mid level data analytics engineers right now include Deloitte, Amazon, and Capital One, based on current listings on Migrate Mate as of August 2026. Hiring at this level comes from a wide range of employers, including technology firms, retailers, financial services companies, and healthcare organizations that depend on data-driven decision making.
Are there remote mid level data analytics engineer jobs?
Yes, remote options are common at this experience level. About 30% of mid level data analytics engineer openings are remote or hybrid as of August 2026, reflecting how broadly distributed data teams have become. Fully on-site roles still exist, particularly at companies with strict data governance requirements or collaborative engineering cultures.
How do I move up to a mid level data analytics engineer role?
The path from entry level to mid level is built on depth and demonstrated ownership over time. Early-career engineers grow into mid level by mastering core tooling, taking on complete project cycles rather than isolated tasks, and showing measurable impact through their work. Documenting outcomes, seeking feedback, and progressively reducing reliance on senior guidance signals readiness for promotion or a lateral move up.
Which industries hire the most mid level data analytics engineers?
Mid Level data analytics engineer roles concentrate in Consulting & Professional Services, Investment & Asset Management, and Accounting & Auditing, based on current listings on Migrate Mate as of August 2026. These sectors drive high demand at this experience level because they combine large data volumes with a need for engineers who can operate independently and turn raw data into reliable, decision-ready outputs.