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Manager Data Analytics Engineer Jobs in Louisiana

Ascentt

Manufacturing Data Analyst

Iowa, LA · On-site

$80 - $100/hr

Ascentt is building cutting-edge data analytics & AI/ML solutions for global automotive and ... Our team solves hard engineering problems at scale, with real-world industry impact. We're hiring ...

New

DPR Construction

Data and AI Project Analyst

Monroe, LA · On-site

$80 - $100/hr

Responsible for coordination with Data Engineering, Solution Architecture, Analytics and offsite ... Manage UAT and QA/QC for deliverables, collaborating with U.S. and offsite teams to incorporate ...

GDIT

TSS Data Analyst Senior

Bossier City, LA · Hybrid

$85K - $107K/yr

The TSS Data and Analytics team uses a variety of tools including Azure and Azure DevOps, AWS, and Tableau. The Tableau dashboards provide program management and financial dashboards to customers ...

Sparks Nissan Kia

Inventory Data Analyst

Monroe, LA · On-site

B achelor's degree in Business Administration, Supply Chain Management, Data Analytics, or a related field. * P roven experience as a data analyst, preferably in a supply chain or inventory ...

Sparks Nissan Kia

Inventory Data Analyst

Monroe, LA · On-site

B achelor's degree in Business Administration, Supply Chain Management, Data Analytics, or a related field. * P roven experience as a data analyst, preferably in a supply chain or inventory ...

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Manager Data Analytics Engineer information

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.

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 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.

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.

What are the most commonly searched types of Data Analytics Engineer jobs in Louisiana?

The most popular types of Data Analytics Engineer jobs in Louisiana are:

What are popular job titles related to Manager Data Analytics Engineer jobs in Louisiana?

For Manager Data Analytics Engineer jobs in Louisiana, the most frequently searched job titles are:

What job categories do people searching Manager Data Analytics Engineer jobs in Louisiana look for?

The top searched job categories for Manager Data Analytics Engineer jobs in Louisiana are:

What cities in Louisiana are hiring for Manager Data Analytics Engineer jobs?

Cities in Louisiana with the most Manager Data Analytics Engineer job openings:

Manager Data Analytics Engineer jobs near you

Data and AI Project Analyst

DPR Construction

Monroe, LA • On-site

Full-time

This job post has expired today. Applications are no longer accepted.

DPR Construction rating

8.0

Company rating: 8.0 out of 10

Based on 37 frontline employees who took The Breakroom Quiz

17th of 80 rated construction

Job description

Job Description
Overview
The Data & AI Project Analyst serves as the field-facing connector between project teams, account leadership, owners/JV partners, and DPR's Technology & Innovation groups-translating business needs into scalable data, analytics, integration, and AI solutions. This role engages early to shape requirements, standardize approaches across projects, coordinate delivery with U.S. and offsite teams, and ensure all data sharing and AI use aligns with governance, legal, and contractual obligations. This is a jobsite-based role, which will require regular travel between all jobsites within a national account.
Data & Development
  • Engage early in pursuit and preconstruction to:
    • Identify owner-mandated technologies
    • Capture data requirements and reporting obligations
    • Surface integration needs and constraints
    • AI opportunity identification
  • Partner with:
    • Integration Managers
    • Account Leadership
    • Project Teams to align on scalable and repeatable approaches
    • Other Account leads
    • Other T&I Groups - (CT, IT, ETS)
  • Align project-level data needs with DPR's Data Strategy and enterprise standards, delivering consistent, flexible solutions that drive measurable impact across the account.
  • Translate business and project needs into clear data, analytics, and integration requirements.
  • This role is primarily field-based, with approximately 75% of time spent on active jobsites and limited opportunity for remote work. This includes participation in key meetings and workgroup meetings at the jobsite.
  • Align AI use cases with owner expectations and contract constraints
  • Advise on feasibility and value of AI-driven solutions

Data & Integration Enablement
  • Influence strategic technology decisions related to data, analytics, AI, and development.
  • Lead conversations with owners, JV partners, and stakeholders on data exchange approaches, including:
    • System access vs data sharing
    • File-based vs platform-based integrations
    • Reporting vs operational use cases
    • Guiding the team through custom analytics and development.
  • Responsible for coordination with Data Engineering, Solution Architecture, Analytics and offsite teams to:
    • Define integration approaches
    • Ensure feasibility and scalability, avoiding one-off or unsustainable solutions
    • Act as a Funnel for requests with US and Offsite teams
  • Manage UAT and QA/QC for deliverables, collaborating with U.S. and offsite teams to incorporate feedback, and own final production readiness and quality.
  • Drive data readiness and integration strategies to support scalable pipelines and enable effective consumption of predictive and generative AI models.
  • Support implementation of standardized data exchange frameworks and templates
  • Ensure all external data sharing aligns with data governance, legal, and contractual requirements
  • Provide hands-on support in analytics and Power BI, iterating on reports, making minor updates, and developing proof-of-concept solutions based on real-time user feedback.

Intake, Prioritization & Coordination
  • Act as the front door for data and development requests at the account level
  • Work with Data & Development Lead - Mega Projects for the prioritization across the accounts
  • Ensure requests are:
    • Clearly defined
    • Properly scoped
    • Prioritized based on business impact
  • Coordinate execution across:
    • Data Engineering
    • Data Analytics
    • AI/ML
    • Software Development
  • Add AI-specific intake criteria (value, risk, data readiness)
  • Prioritize AI initiatives alongside analytics and development work
  • Coordinate across AI/ML teams for model development and deployment
  • Track progress, manage expectations, and communicate updates to stakeholders
  • Escalate risks, conflicts, and capacity constraints when needed

Standardization & Reuse
  • Identify opportunities to:
    • Reuse existing dashboards, pipelines, and integrations
    • Avoid duplication across projects and accounts
  • Promote standardized approaches for:
    • Data mapping
    • Integration patterns
    • Reporting structures
    • Drive implementation of AI use cases by prioritizing reusable models, prompts, and workflows, and minimizing one-off, non-scalable solutions.
  • Contribute to the development of templates and best practices for mega projects.

Project Onboarding & Enablement
  • Support setup of new projects by:
    • Aligning on data requirements and integrations
    • Facilitating access to systems and tools
    • Coordinating onboarding workflows (data, analytics, reporting)
    • Work with Integration Managers to understand account-level and project-level technology stacks including:
      • DPR standard tools
      • Owner-mandated systems
      • JV partner systems
      • AI/ML tools, platforms, and model usage
      • Track approved vs non-approved AI technologies
      • Identify implications of introducing AI into project tech stacks
  • Partner with Integration Managers to deliver and support project landing pages, access management workflows, standardized setup processes, and effective analytics storytelling for project teams.
  • Facilitate rollout of dashboards and tools, including training and enablement for internal and external project teams for onboarding, access, and effective data usage.
  • Champion the use of existing tools and platforms across project teams to drive consistency and maximize value.
  • Assess the technology stack and identify deviations from standards, evaluating downstream impacts on data, development, AI, integrations, cost, and support.

Data Governance & Compliance
  • Ensure all data activities align with:
    • DPR data governance policies
    • NDA & Contractual obligations
    • Client data requirements
    • Ensure AI usage complies with client data restrictions and contracts
    • Align with AI governance policies (data privacy, model usage, vendor constraints)
  • Help define:
    • What data can be shared
    • How it can be used (internal vs external)
    • Where it should be stored (e.g., warehouse-first approach)
  • Support documentation of:
    • Data definitions
    • Data sources
    • Integration logic

Technical Skills
  • Working knowledge of Data and AI
    • Basic understanding of AI/ML and their capabilities
    • Data gathering and quality issues
    • Power BI
  • Business process and systems thinking
    • Map workflows and identify inefficiencies
    • Understand system dependencies
  • Support integration of AI into existing DPR workflows and systems, from adoption to deployment
  • Ability to assist with piloting AI and data solutions on projects, gather user feedback, identify adoption barriers, and refine workflows to ensure tools deliver real-world value.
  • Maintain a working knowledge of AI, data capabilities, and limitations to evaluate opportunities realistically. Ask critical questions about data availability, problem fit, and automation value while leveraging common tools such as dashboards and reporting platforms.

Qualifications
  • Minimum of 4 years of experience in a relevant data analytics/integration delivery role with a strong Power BI background and experience in the construction industry.
  • Proven track record of managing stakeholder expectations and delivering data solutions aligned with business priorities.
  • Experience with modern data platforms like Snowflake and Microsoft Fabric.
  • Experience with mapping, documenting, and analyzing business workflows to identify inefficiencies and gaps.
  • Ability to translate ambiguous project team requests into clear, actionable use cases with defined data sources and success criteria.
  • Strong problem-solving skills and ability to troubleshoot complex data issues.
  • Excellent communication skills, with the ability to work collaboratively in a team environment.
  • Experience working with or coordinating with overseas teams is a strong plus

DPR Construction is a forward-thinking, self-performing general contractor specializing in technically complex and sustainable projects for the advanced technology, life sciences, healthcare, higher education and commercial markets. Founded in 1990, DPR is a great story of entrepreneurial success as a private, employee-owned company that has grown into a multi-billion-dollar family of companies with offices around the world.
Working at DPR, you'll have the chance to try new things, explore paths and shape your future. Here, we build opportunity together-by harnessing our talents, enabling curiosity and pursuing our collective ambition to make the best ideas happen. We are proud to be recognized as a great place to work by our talented teammates and leading news organizations like U.S. News and World Report, Forbes, Fast Company and Newsweek.
Explore our open opportunities at www.dpr.com/careers.

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