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Manager Data Analytics Engineer Jobs in Georgia (NOW HIRING)

Emanuelchamber

Manager, Data Platform

Peachtree City, GA · On-site

$140 - $190/hr

Manager, Data Platform, Peachtree City, Georgia The Manager, Data Platform is a player‑coach ... Analytics & AI Enablement * Enable BI teams, data scientists, and citizen developers through ...

New

4pconsultinginc

Data Analytics Analyst III

Atlanta, GA · On-site

SQL & Data Engineering * Develop advanced SQL queries across relational databases: * Azure SQL ... Metadata management * Data stewardship * Familiarity with Spark SQL or Databricks SQL. Technical ...

Workday, Inc.

Sr Analytics Engineer

Atlanta, GA · On-site

$160.06 - $216.50/hr

... analytics, prompt engineering for large language models, and intelligent data discovery while ... management. * Collaborate closely with the Data Governance team to define policies and influence ...

Interfor

Manager, Data Platform

Peachtree City, GA · On-site

$140 - $190/hr

Manager, Data Platform, Peachtree City, Georgia The Manager, Data Platform is a player-coach ... Analytics& AI Enablement * Enable BI teams, data scientists, and citizen developers through ...

CRH

Manager, Data Engineering

Atlanta, GA · On-site

Manager, Data Engineering AMAT Atlanta, Georgia, United States Job ID: 525350 CRH's Americas ... The ideal candidate is a pragmatic, analytical leader with strong technical expertise and excellent ...

Interfor

Manager, Data Platform

Peachtree City, GA · On-site

Manager, Data Platform, Peachtree City, Georgia The Manager, Data Platform is a player-coach ... Analytics& AI Enablement * Enable BI teams, data scientists, and citizen developers through ...

HD Supply

Data Analytics Specialist

Atlanta, GA · On-site

Leverage innovative analytical techniques to uncover patterns and trends in data. Utilize data ... Collaborates with internal and external stakeholders to manage data logistics, including data ...

HD Supply

Data Analytics Specialist

Atlanta, GA · On-site

Leverage innovative analytical techniques to uncover patterns and trends in data. Utilize data ... Collaborates with internal and external stakeholders to manage data logistics, including data ...

Workday, Inc.

Sr Analytics Engineer

Atlanta, GA · On-site

$160K - $216K/yr

... analytics, prompt engineering for large language models, and intelligent data discovery while ... backlog management, ensuring efficient and iterative delivery. Collaborate closely with our Data ...

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All JobsData Analytics Engineer JobsManager Data Analytics Engineer JobsManager Data Analytics Engineer Jobs in Georgia

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 Georgia?

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

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

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

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

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

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

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

Manager Data Analytics Engineer jobs near you

Data Platform & Analytics Engineer

Altus Fire and Life Safety

Atlanta, GA • On-site

$130K - $150K/yr

Full-time

Posted 12 days ago

Job description

Altus Fire & Life Safety is a full-service fire and life safety services platform. We offer a complete suite of solutions, from the design, engineering, installation, and servicing of state-of-the-art fire and life safety systems to training, consulting, crisis management and business continuity services.
Altus Fire & Life Safety is accelerating its Data and AI Journey. We are building a modern warehouse with a partner now, and we are looking for a  hands-on Data Platform & Analytics Engineer who can help turn that effort into trusted, usable data for the business.
This role is for someone who wants to build the data foundation, not inherit a mature one. You will work with consultants, colleagues, and the executive team to validate core KPIs, build trusted dbt models and data marts, define data-quality rules, and create the semantic layer we need for reporting, analytics, and future AI use cases. The work will be hands-on, sometimes messy, and highly visible.
We value our well-being just as much as our hard work.  We are committed to a holistic approach towards benefits plans and programs that support the mental, physical and financial well-being of our team members.
Salary Range:  $130,000 - $150,000ResponsibilitiesWhat You Will Do
  • Build the Trusted Data Foundation: Develop core dbt models, staging layers, data marts, and reusable business logic in Snowflake so teams can trust the numbers they use to run the business.
  • Partner with consultants and Internal Leaders: Be the day-to-day Altus counterpart to our warehouse partner while working directly with executive, branch, and FP&A stakeholders to make sure the data model reflects how the business actually operates.
  • Validate Core KPIs: Help turn KPI ideas into definitions people can trust: source of record, grain, numerator, denominator, exclusions, timing rules, ownership, and known limitations.
  • Build Data Quality Into the Model: Add tests, reconciliation checks, documentation, and exception reporting so bad data is visible and explainable instead of quietly buried in a dashboard.
  • Design for AI-Ready Data: Structure models, dimensions, semantic definitions, and metadata so future AI tools can answer business questions using governed, trusted data rather than ad hoc logic.
  • Deliver Practical Business Use Cases: Focus first on branch performance, labor/productivity, sales pipeline, and FP&A needs. The point is not just to move data; it is to help leaders see what is happening and what to do next.
What You Won’t Do
  • Operate as a Passive Ticket-Taker: You will not simply receive dashboard requests and write one-off SQL. You will be expected to ask why, clarify definitions, and help shape better data products.
  • Own BI Polish Alone: You do not need to be a dashboard wizard. We care more about trusted models, clear metric definitions, and useful decision workflows than highly designed visualizations.
  • Run a Large Team on Day One: This is a high-impact individual contributor role. Over time, the right person could grow into a broader data lead role as the function matures.

Our Core Tech Stack
  • Warehouse: Snowflake
  • Ingestion: Fivetran
  • Transformation and Modeling: dbt, SQL
  • Analysis and Automation: Python
  • BI / Applications: To be determined; early use cases may include lightweight Streamlit apps or other fit-for-purpose reporting layers
  • Ways of Working: Git-based development, code review, testing, documentation, and close partnership with business stakeholders

Required Skills
  • Experience: 4+ years in analytics engineering, data engineering, BI engineering, or a similar hands-on data role. We care more about judgment and ownership than exact title history.
  • SQL and dbt Strength: Strong modern SQL skills and practical experience building, testing, documenting, and maintaining dbt models.
  • Business Partnership: Proven ability to work with non-technical leaders, unpack ambiguous requests, and translate business questions into modeled data and repeatable reporting logic.
  • Modeling Judgment: Strong understanding of grain, source of record, dimensions, fact tables, marts, semantic layers, and why small definition choices can materially change the number.
  • Data Quality Mindset: Strong instincts for testing, reconciliation, exception handling, lineage, and making exclusions visible rather than silent.
  • Ownership Mindset: You do not wait for someone else to resolve ambiguity. You identify the open question, find the right owner, document the decision, and move the work forward.
  • AI Pragmatism: You are interested in AI as a force multiplier, but you understand that AI is only useful when the underlying data, definitions, and governance are trustworthy.

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