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Senior Database Engineer Jobs in Georgia (NOW HIRING)

Kiongroup

Senior Data Engineer

Atlanta, GA · On-site

$133K - $204K/yr

We are seeking a dynamic and highly skilled Senior Data Engineer who has extensive experience ... design data models, database schemas and data storage solutions. * Proactively identify and ...

Monitise

Senior Cybersecurity Data Engineer

Alpharetta, GA · On-site

$109K - $182K/yr

Job Title Senior Cybersecurity Data Engineer About your role: You will interface with security Big ... Fundamental knowledge of firewalls, networking, operating systems, databases, and storage at a ...

TIER4 GROUP

Senior Data Engineer

Atlanta, GA · Hybrid

$100K - $136K/yr

Data Engineer Location: Atlanta, Georgia (Hybrid Remote- 2 days onsite/ 3 days remote) Job Type ... Integrate data from various sources, including databases, APIs, and external systems. * Collaborate ...

Guidehouse

Senior Data Engineer

Atlanta, GA

$80K - $133K/yr

Guidehouse seeks a Senior Data Engineer to design, develop, and optimize modern data platforms ... Experience working with relational and non-relational databases, including data modeling and query ...

New

T-Mobile

Sr Engineers, Data

Atlanta, GA · On-site

$101K - $138K/yr

Senior Engineers, Data located in Atlanta, GA will develop data engineering solutions, including ... Applying SQL, relational modeling, and database development to build curated datasets, dimensional ...

New

OVA.Work

Senior DS engineer

Alpharetta, GA · On-site

$100K - $136K/yr

Required : • Strong knowledge of SQL and database systems • Experience with Python, Scala, or ... and DevOps practices • Problem-solving mindset • Strong communication skills • Team ...

OVA.Work

Senior data engineer

Alpharetta, GA · On-site

$100K - $136K/yr

Required : • Strong knowledge of SQL and database systems • Experience with Python, Scala, or ... and DevOps practices • Problem-solving mindset • Strong communication skills • Team ...

Dolby

Senior Database Researcher

Atlanta, GA · On-site

... engineering, such as AI/ML, algorithms, digital signal processing, audio engineering, image ... We're looking for talented database systems and big data management researchers who are excited to ...

Infor

Cloud Database Administrator, Sr.

Atlanta, GA · On-site

$47.75 - $65.75/hr

Cloud Database Administrator, Sr. Department: SaaS Employment Type: Full Time Location: Atlanta ... You'll work closely with cloud engineers, architects, and DevOps teams to deliver high-performance ...

Gordon Food Service

Senior Data Engineer

Atlanta, GA · Hybrid

$101K - $138K/yr

The Senior Data Engineer guides the development of GFS' Data Platform consisting of the data lake ... relational database management/optimization (specifically PostgreSQL and SQL Server). * Highly ...

AgileEngine

Senior Data Engineer ID75059

Boston, GA · On-site

$87K - $118K/yr

ABOUT THE ROLE We are looking for a Senior Data Engineer to design and build scalable data lakes ... database technologies (SQL, NoSQL, and Lakehouse architectures); - Proven ability to work with 3rd ...

Aimpoint Digital

Senior Data Engineer 2026 - US

Atlanta, GA · On-site +1

$101K - $138K/yr

As a Senior Data Engineer, you will be expected to work independently on client engagements, take ... relational databases and query languages * 3+ years building data pipelines in production and ...

Altamira Technologies Corp.

Senior Data Engineer

Gordon, GA · On-site

$99K - $135K/yr

An Altamira Data Engineer is an integral member of an analytic and engineering team. The data ... databases efficiently using SQL • Experience with tradecraft and publication; ability to ...

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Senior Database Engineer information

See Georgia salary details

$68.4K

$106.7K

$147.8K

How much do senior database engineer jobs pay per year?

As of Aug 12, 2026, the average yearly pay for senior database engineer in Georgia is $106,669.00, according to ZipRecruiter salary data. Most workers in this role earn between $89,500.00 and $121,600.00 per year, depending on experience, location, and employer.

What are some common challenges senior database engineers face when managing large-scale databases, and how are they typically addressed?

Senior Database Engineers often encounter challenges such as ensuring database performance under heavy loads, maintaining data integrity during migrations, and optimizing queries for efficiency. Addressing these issues usually involves proactive monitoring, implementing indexing strategies, and collaborating closely with development teams to design scalable database schemas. Regularly updating skills to keep up with new database technologies and security best practices is also essential for tackling these challenges effectively.

What is the difference between Senior Database Engineer vs Database Administrator?

AspectSenior Database EngineerDatabase Administrator
Primary FocusDesigning, developing, and optimizing database systemsMaintaining, backing up, and securing databases
Skills & CertificationsSQL, database architecture, performance tuning, certifications like Oracle or Microsoft SQL ServerDatabase management, backup/recovery, security, certifications like Oracle DBA or Microsoft Certified Database Administrator
Work EnvironmentDevelopment teams, data engineering projects, system designOperational teams, system maintenance, troubleshooting
Industry UsageUsed across tech, finance, healthcare for database developmentCommon in enterprise IT, government, and large organizations for database upkeep

While both roles work closely with databases, a Senior Database Engineer primarily focuses on designing and optimizing database systems, whereas a Database Administrator handles daily maintenance, security, and backups. The roles complement each other but differ in scope and responsibilities.

What are the key skills and qualifications needed to thrive as a senior database engineer, and why are they important?

A Senior Database Engineer needs advanced knowledge of database architecture, SQL, performance tuning, and a degree in computer science or a related field. Expertise in tools like Oracle, MySQL, PostgreSQL, database clustering, and relevant certifications such as Microsoft Certified: Azure Database Administrator Associate are typical requirements. Strong problem-solving, analytical thinking, and effective communication skills help them excel in managing complex data environments and collaborating with development teams. These capabilities are crucial for ensuring robust, scalable, and secure data solutions that meet organizational needs.

What is a senior database engineer?

A Senior Database Engineer is an experienced IT professional responsible for designing, implementing, maintaining, and optimizing database systems within an organization. They ensure databases are secure, reliable, and perform efficiently to meet business needs. Senior Database Engineers often lead projects, mentor junior staff, and collaborate with developers and system administrators to support data-driven applications. Their expertise is crucial for data integrity, scalability, and disaster recovery planning.
What are the most commonly searched types of Database Engineer jobs in Georgia? The most popular types of Database Engineer jobs in Georgia are:
What are popular job titles related to Senior Database Engineer jobs in Georgia? For Senior Database Engineer jobs in Georgia, the most frequently searched job titles are:
What job categories do people searching Senior Database Engineer jobs in Georgia look for? The top searched job categories for Senior Database Engineer jobs in Georgia are:
What cities in Georgia are hiring for Senior Database Engineer jobs? Cities in Georgia with the most Senior Database Engineer job openings:
What are popular job titles related to Senior Database Engineer jobs in GA? For Senior Database Engineer jobs in GA, the most frequently searched job titles are:
Senior Database Engineer jobs near you
Infographic showing various Senior Database Engineer job openings in Georgia as of August 2026, with employment types broken down into 87% Full Time, 6% Part Time, 1% Temporary, and 6% Contract. Highlights an 86% Physical, 5% Hybrid, and 9% Remote job distribution, with an average salary of $106,669 per year, or $51.3 per hour.

Senior Data Engineer

Intercontinental Exchange Holdings, Inc.

Atlanta, GA • On-site

$101K - $138K/yr

Full-time

Re-posted 29 days ago

Job description

Overview
Job Purpose
ICE Data Services (an Intercontinental Exchange company) is seeking a Senior Data Engineer to join its Data Impact & Innovation team. This team supports a variety of reference data, index, climate finance, and alternative data products. The role contributes to the data platforms and pipelines that help the financial sector understand and respond to carbon transition risk, physical risk, and related challenges.
Our team maintains a global-scale geospatial data platform in Google BigQuery, holding many terabytes of data across carbon transition risk, physical climate risk, and social/demographic features - feeding analytical products for fixed income and real estate financial instruments, supporting the ambitious product roadmap for ICE Climate and other data products. Our engineering stack includes:
  • Orchestration: Airflow, moving toward composable task abstractions over a shared pipeline framework
  • Transformation: dbt, and other data lineage and DQA tools, primarily using Google BigQuery
  • Geospatial processing: Python (GeoPandas, Shapely, GeoAlchemy2 against PostGIS) for vector operations, and R
  • Execution and compute environments: Hybrid across Google Cloud Platform and on-premise RHEL Linux infrastructure
  • Ingestion: Third-party vendor feeds via API, SFTP, cloud storage, and database replication

Typical engineering challenges include working with data science and climate science teams in operationalizing trained models and data pipelines, absorbing upstream vendor corrections and historical restatements without corrupting downstream artifacts, scaling raster x vector joins at terabyte scale, evolving schemas and spatial-indexing strategies as data sources broaden, and balancing long-running batch workflows against emerging sub-daily refresh cadences.
Responsibilities
  • Take significant components of the data platform from "works" to "mature" - tightening reliability, observability, cost/performance characteristics, and operational discipline across our ingestion, transformation, and serving layers.
  • Establish and foster adoption of technical standards for the team's work - including Airflow DAG structure, dbt model layout, BigQuery schema and partitioning conventions, pipeline testing practices, and deployment workflows.
  • Lead technical design discussions, mentor other data engineers through code review, pairing, and design-doc review, and grow them along their career path.
  • Act as a technical point of contact for cross-functional initiatives - partnering with data science, climate science, product, and infrastructure colleagues to drive forward decisions and make tradeoffs explicit.
  • Deliver day-to-day work across the stack above - authoring Airflow DAGs and dbt models, contributing geospatial processing capabilities, and shipping cleanly partitioned, audit-friendly outputs from ingestion through serving.
  • Support data science and climate science teams by helping design the tooling, training, and validation environments, and by deploying their trained models into production.
  • Effectively leverage AI and LLM-based developer tooling to accelerate development workflows and improve code quality.
  • Identify opportunities to improve and optimize data pipelines - for speed, cost, robustness, integrity, and operational simplicity.
  • Work with business analysts, product management, and adjacent engineering teams to understand and refine new data requirements.

Knowledge and Experience
  • 5+ years of professional experience as a data engineer, with a track record of architecting, shipping, and operating production data pipelines end-to-end.
  • Experience mentoring and developing other data engineers - through code review, pairing, design discussions, and career coaching.
  • Ability to establish and foster adoption of technical standards.
  • A habit of actively monitoring, evaluating, and prototyping emerging big-data, geospatial, and machine-learning technologies and platforms - staying conversant in advances across cloud data engines, geospatial libraries and standards, and ML/MLOps frameworks - and bringing the most promising into the team's design discussions, evaluations, and adoption decisions.
  • Strong system-design judgment across the tradeoff space of performance, cost, maintainability, and auditability
  • Comfort scoping, decomposing, and delegating work for other engineers.
  • Strong written and verbal communication - able to translate technical tradeoffs for senior business, product, and client stakeholders.
  • Deep fluency in modern, typed Python as a primary working language, including comfort with type-driven design (e.g. Pydantic v2).
  • Strong SQL background, including experience partitioning, clustering, and performance-tuning queries on modern cloud warehouses - Google BigQuery experience strongly preferred.
  • Production experience with dbt for managing warehouse transformations, and with Airflow (or a comparable orchestrator) for workflow orchestration.
  • Solid grounding in geospatial data engineering - Python tooling (GeoPandas, Shapely), spatial databases (PostGIS), raster processing, or adjacent skills.
  • A systems-thinking orientation: anticipates cascading effects of upstream data changes, schema evolution, and vendor corrections; designs pipelines with observability, auditability, and graceful failure in mind.
  • Comfort owning production incidents and debugging distributed systems.
  • Experience working cooperatively with systems, network, and infrastructure engineering and operations teams to ensure proper monitoring, alerting, and incident response workflows.
  • Demonstrated ability to integrate AI/LLM coding assistants productively - treating them as a force multiplier rather than a substitute for judgment.
  • Curiosity about the financial and climate/geospatial domains and contexts the team operates in.

Preferred Knowledge and Experience
  • Well-versed in and opinionated about the modern Python ecosystem.
  • Exposure to columnar and lakehouse technologies (Parquet, ClickHouse, DuckDB).
  • Working understanding of data lineage, data quality validation, and metadata/cataloging frameworks.
  • Prior experience in a hybrid cloud + on-premise environment, and with full software development lifecycle (SDLC) best practices and processes.
  • Prior exposure to ML deployment workflows - supporting data science teams with training tooling and/or model-serving infrastructure.
  • Familiarity with R, particularly geospatial packages.

#LI-HR1 #LI-ONSITE
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Intercontinental Exchange, Inc. is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to legally protected characteristics.

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