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Manager Data Analytics Engineer Jobs in Indiana (NOW HIRING)

Munich Re

Technical Architect - Data, Analytics & AI

Carmel, IN · Hybrid

$63.75 - $81.75/hr

Define and maintain technical standards for enterprise data management, analytics platforms, and AI ... Collaborate with Data Science, Engineering, Security, and Risk teams to enable scalable, secure ...

Serco

Manager Data Engineering

Indianapolis, IN · On-site

Partner with program managers, solution architects, data scientists, analysts, cybersecurity staff ... Ensure data engineering solutions comply with applicable federal security, privacy, and compliance ...

POLYWOOD

VP of Data & Analytics

Syracuse, IN · On-site

You'll own the enterprise data platform, lead a team of data and analytics engineers, and manage embedded analysts across the organization who sit close to the business units they serve. Critically ...

Beacon Health System

Data Engineer

Granger, IN · On-site

$102.70K - $123.30K/yr

Reports to the Manager, Business Intelligence. The Data Engineer delivers insights and supports ... Collecting, organizing, analyzing, and disseminating significant amounts of information with ...

Pae

Mission Support & Data Analytics Coordinator

Crane, IN · On-site

$93K - $99.50K/yr

Portfolio Coordination - Schedule, manage, and facilitate high-level meetings across SCALE, MEST ... Minimum Requirements: * BS in Data Analytics, Engineering, CS, Operations Research, Business ...

Beacon Health System

Data Engineer

Granger, IN · On-site

$102.70K - $123.30K/yr

Reports to the Manager, Business Intelligence. The Data Engineer delivers insights and supports ... Collecting, organizing, analyzing, and disseminating significant amounts of information with ...

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Manager Data Analytics Engineer information

What are the key skills and qualifications needed to thrive as a Manager Data Analytics Engineer, and why are they important?

To thrive as a Manager Data Analytics Engineer, you need a strong background in data engineering, analytics, and leadership, typically with a degree in computer science or a related field. Familiarity with tools like SQL, Python, data warehousing platforms (e.g., Snowflake, Redshift), and certifications in cloud technologies or data management are common requirements. Excellent communication, problem-solving, and team management skills set top performers apart in this role. These competencies are essential for driving data strategy, ensuring data quality, and leading analytics teams to deliver actionable business insights.

How does a Manager Data Analytics Engineer typically balance technical project work with team leadership responsibilities?

As a Manager Data Analytics Engineer, you are expected to split your time between overseeing complex analytics engineering tasks and guiding your team’s development. This involves setting project priorities, conducting code reviews, and ensuring data solutions align with business goals, while also mentoring team members and facilitating collaboration with stakeholders like data scientists and business analysts. Successful managers often establish clear communication channels and delegate tasks effectively, so they can stay hands-on with key projects while supporting the professional growth of their team.

What is a Manager Data Analytics Engineer?

A Manager Data Analytics Engineer is a professional who leads a team of data analytics engineers responsible for designing, building, and maintaining data systems and analytics solutions. They oversee data pipeline development, ensure data quality, and collaborate with stakeholders to translate business requirements into technical solutions. In addition to technical expertise, they manage project timelines, mentor team members, and help drive data-driven decision-making across the organization.

What is the difference between Manager Data Analytics Engineer vs Data Analytics Engineer?

AspectManager Data Analytics EngineerData Analytics Engineer
Required CredentialsBachelor's or Master's in Data Science, Analytics, or related field; often leadership experienceBachelor's or Master's in Data Science, Analytics, or related field
Work EnvironmentLeads teams, manages projects, collaborates with stakeholdersDevelops data models, analyzes data, implements solutions
Employer & Industry UsageUsed in tech, finance, healthcare, and large enterprisesCommon in similar industries, often within data teams

The main difference is that a Manager Data Analytics Engineer oversees teams and projects, focusing on leadership and strategic planning, while a Data Analytics Engineer primarily develops and implements data solutions. Both roles require strong technical skills, but the manager role adds a layer of team management and stakeholder communication.

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Manager Data Analytics Engineer jobs near you
Senior Analytics Engineer Ecommerce/Manufacturing

Senior Analytics Engineer Ecommerce/Manufacturing

Harnham

Indianapolis, IN • Hybrid

$99.90K - $137.20K/yr

Other

This job post has expired 1 day ago. Applications are no longer accepted.

Job description

Senior Analytics Engineer
Overview
A rapidly growing consumer products company is seeking a Senior Analytics Engineer to help build and scale a modern data platform. This role sits at the intersection of analytics engineering, data infrastructure, and business intelligence, enabling teams across the organization to make data-driven decisions.
The company operates a U.S.-based manufacturing environment and a strong direct-to-consumer ecommerce platform. As the organization continues to scale, the data function is being built from the ground up, creating an opportunity for a hands-on engineer to shape the architecture, pipelines, and analytics capabilities of the business.
Responsibilities
Data Platform Development
  • Build, maintain, and optimize data models using SQL and DBT
  • Support migration and development of a centralized data warehouse environment
  • Design scalable data architecture and transformation layers
  • Improve reliability, performance, and maintainability of analytics infrastructure
Data Pipeline Engineering
  • Develop and maintain ETL/ELT pipelines using modern data tools
  • Expand and optimize ingestion pipelines from operational systems
  • Write custom workflows and integrations using Python
  • Ensure data quality, monitoring, and pipeline stability
Business Intelligence & Analytics
  • Develop and maintain dashboards and reporting solutions
  • Enable self-service analytics for business teams
  • Work directly with stakeholders to translate business needs into data solutions
  • Support analytics across key functions including:
  • Supply chain
  • Ecommerce performance
  • Marketing analytics
  • Sales performance
  • Forecasting and operations
Data Governance & Reliability
  • Establish trusted datasets and consistent data definitions
  • Improve data documentation and discoverability
  • Troubleshoot data issues and analytics requests across teams
  • Ensure long-term scalability of the analytics ecosystem
Required Qualifications
  • 4+ years of experience working with SQL
  • 4+ years of experience using DBT
  • 4+ years of experience building dashboards and BI solutions
  • Experience building and managing data pipelines and ETL workflows
  • Strong understanding of data warehousing concepts
  • Ability to work independently in a fast-paced, evolving environment
  • Strong communication skills and experience collaborating with non-technical stakeholders
Preferred Qualifications
  • Experience working with BigQuery
  • Experience building dashboards in Looker
  • Pythonfor data workflows or ingestion pipelines
  • Experience with ecommerce analytics
  • Experience analyzing Shopify or similar commerce platforms
  • Experience working with manufacturing or supply chain data
Ideal Candidate Background
Strong candidates often come from:
  • Ecommerce organizations
  • Manufacturing companies
  • Businesses operating direct-to-consumer sales models
  • Mid-sized companies where individuals have broad ownership of the data stack
Experience analyzing
  • Ecommerce sales performance
  • Supply chain operations
  • Marketing attribution
  • Product and operational data
Work Environment
  • Hybrid work model with 2-3 days per week in office
  • Collaboration with a small technical team including IT and data science
  • Fast-paced environment with significant opportunity to influence the company's data strategy
  • High level of autonomy and ownership over technical solutions
What We're Looking For
  • Curious and evidence-driven
  • Comfortable working with ambiguity
  • Self-directed and proactive
  • Passionate about learning new technologies
  • A strong problem solver who enjoys building scalable systems

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