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Manager Data Engineering Jobs in Georgia (NOW HIRING)

TOPSYSIT

Data Engineer

Atlanta, GA · On-site

$110K - $132K/yr

You will build scalable ETL/ELT pipelines and manage cloud data warehousing solutions ... Requirements * 3+ years of production data engineering experience. * Hands-on expertise in ...

IRB USA Inspire Resources

Lead Data Engineer

Atlanta, GA · On-site

$110K - $132K/yr

Lead/guide multiple technical data engineering team members * Lead by example - designing, building, maintaining and using of our platforms and services to manage data * Design, develop, deploy ...

LVTLABS

Data Engineering Lead

Alpharetta, GA · On-site

... database management, and data integration using Informatica and PL\/SQL . \n \n \n * Team ... Guide and mentor a team of engineers and developers, offering technical direction, support, and ...

Genpact

Analyst - Data Engineering 5A

Atlanta, GA · On-site

... Data Management Professional - RiversandRiversand, Cloudera Certified Professional (CCP) Data ... Azure Data Engineer Associate - MicrosoftMicrosoft, Oracle Database 12c Certified Implementation ...

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Manager Data Engineering information

What are the roles and responsibilities of a manager data engineering?

A Manager Data Engineering oversees teams that design, build, and maintain data infrastructure and pipelines for organizations. They are responsible for ensuring the efficient flow and storage of data, implementing best practices in data management, and collaborating with stakeholders to meet business data needs. Additionally, they mentor and guide data engineers, manage project timelines, and ensure data security and quality standards are met. Their role often involves strategic planning to enable data-driven decision making across the company.

What are the key skills and qualifications needed to thrive as a manager data engineering?

To thrive as a Manager Data Engineering, you need expertise in data architecture, advanced analytics, and leadership, typically supported by a degree in computer science or a related field. Familiarity with big data tools (like Hadoop, Spark), data warehousing systems, cloud platforms (AWS, Azure), and certifications such as AWS Certified Data Analytics are highly valued. Strong communication, problem-solving, and team management skills help drive project success and foster collaboration. These skills ensure effective data solutions, alignment with business goals, and the ability to lead and grow high-performing engineering teams.

How does a manager data engineering typically collaborate with data scientists and business stakeholders?

A Manager of Data Engineering often serves as a bridge between technical teams and business stakeholders. They work closely with data scientists to ensure that data pipelines and infrastructure meet analytical needs, while also translating business requirements into actionable engineering solutions. Regular coordination meetings, clear documentation, and cross-functional projects are common, enabling seamless collaboration and alignment on goals. This role requires strong communication skills and the ability to balance technical priorities with business objectives.

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

AspectManager Data EngineeringData Engineer
Required CredentialsBachelor's or Master's in CS, Data Science, or related; often leadership experienceBachelor's or higher in CS, IT, or related; technical certifications optional
Work EnvironmentTeam leadership, project management, strategic planningData pipeline development, coding, data modeling
Employer & Industry UsageTech companies, finance, healthcare, where data teams are commonData-focused roles across various industries

The main difference is that Manager Data Engineering oversees data teams and projects, focusing on strategy and leadership, while Data Engineers handle the technical implementation of data pipelines and infrastructure. Managers typically have more experience and leadership skills, whereas Data Engineers are more hands-on with coding and data architecture.

What are the most commonly searched types of Data Engineering jobs in Georgia?

The most popular types of Data Engineering jobs in Georgia are:

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

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

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

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

What cities in Georgia are hiring for Manager Data Engineering jobs?

Cities in Georgia with the most Manager Data Engineering job openings:

Manager Data Engineering jobs near you
Infographic showing various Manager Data Engineering job openings in Georgia as of August 2026, with employment types broken down into 88% Full Time, 11% Part Time, and 1% Contract. Highlights an 79% Physical, 3% Hybrid, and 18% Remote job distribution.

Data Engineer

Atlanta, GA • On-site

TOPSYSIT
See more jobs at TOPSYSITexternal

$110K - $132K/yr

Other

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

Job description

Data Engineer (Databricks / Snowflake / Azure)

LOOKING ONLY ON W2

Overview

We are looking for a Data Engineer to design and maintain enterprise data platforms using Databricks, Snowflake, and Azure. You will build scalable ETL/ELT pipelines and manage cloud data warehousing solutions.

Responsibilities

  • Design and deploy batch and streaming data pipelines u
  • sing Databricks, Snowflake, and Azure Data Factory.
  • Write ETL/ELT workflows using Python, PySpark, and advanced SQL for large-scale datasets.
  • Manage data lake and warehouse architectures on Azure (ADLS, Synapse), Databricks (Delta Lake, Unity Catalog), and Snowflake.
  • Optimize Snowflake query performance, storage, clustering, and partitioning.
  • Implement dimensional data models (star/snowflake schemas) and CI/CD pipelines via Git and Azure DevOps.
  • Partner with analysts and stakeholders to deliver reliable, production-ready data products.

Requirements

  • 3+ years of production data engineering experience.
  • Hands-on expertise in Databricks, Snowflake, and Azure.
  • Strong proficiency in Python, PySpark, and SQL query optimization.
  • Proven background in data modeling, warehousing, and pipeline orchestration (e.g., ADF, Airflow, dbt).
  • Experience with Git, CI/CD practices, and basic data governance/security standards.

Apply