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Senior Data Engineer Jobs in Decatur, GA (NOW HIRING)

Troutman Pepper

Senior Data Engineer

Atlanta, GA · Remote

$101K - $138K/yr

The Senior Data Engineer is responsible for analyzing, validating, cleansing, and performing ETL of enterprise data into the firm's finance applications, as well as creating validation reports ...

Honeywell

Sr Data Engineer

Atlanta, GA · On-site

$110K - $132K/yr

As a Senior Data Engineer, you will be part of a high-performing global team delivering advanced AI and data solutions for Honeywell's industrial customers, with a focus on IoT and real-time data ...

Honeywell

Sr Data Engineer

Atlanta, GA

$110K - $132K/yr

As a Senior Data Engineer, you will be part of a high-performing global team delivering advanced AI and data solutions for Honeywell's industrial customers, with a focus on IoT and real-time data ...

Honeywell

Sr Data Engineer

Atlanta, GA · On-site

$110K - $132K/yr

As a Senior Data Engineer, you will be part of a high-performing global team delivering advanced AI and data solutions for Honeywell's industrial customers, with a focus on IoT and real-time data ...

QGenda

Senior Data Engineer

Atlanta, GA · On-site

$101K - $138K/yr

About Your Role As a Senior Data Engineer, you will design, build, and optimize the data platform, including pipelines, models, and infrastructure that power analytics, reporting, and data-driven ...

Tata Consultancy Services

Senior Data Engineer

Atlanta, GA · On-site

$101K - $138K/yr

Tata Consultancy Services is seeking a Senior Data Engineer with strong expertise in Lakehouse architecture to design and build scalable data pipelines on AWS. The role focuses on developing high ...

Tata Consultancy Services

Senior Data Engineer

Atlanta, GA · On-site

$101K - $138K/yr

Tata Consultancy Services is seeking a Senior Data Engineer with strong expertise in MongoDB and data serving layers to design and enable scalable, high-performance data access for enterprise ...

Delta Dental Ins.

Senior Data Engineer

Alpharetta, GA · On-site

$160K - $165K/yr

Senior Data Engineer Location: 1130 Sanctuary Parkway, Alpharetta, GA 30009; Must live within reasonable commuting distance from HQ and able to appear in office as required. Salary Range: $160,056/yr ...

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, analytics, enterprise data sandboxes, and certified internal data products. Identifies and ...

Scientific Games

Senior Data Engineer

Alpharetta, GA · On-site

$103K - $140K/yr

Position Summary Scientific Games is hiring a Senior Data Engineer to help build and modernize the lottery data platform supporting reporting, analytics, data science, and future AI capabilities. You ...

Scientific Games

Senior Data Engineer

Alpharetta, GA

$103K - $140K/yr

Position Summary Scientific Games is hiring a Senior Data Engineer to help build and modernize the lottery data platform supporting reporting, analytics, data science, and future AI capabilities. You ...

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All JobsData Engineer JobsSenior Data Engineer JobsSenior Data Engineer Jobs in Decatur, GA

Senior Data Engineer information

See Decatur, GA salary details

$79.1K

$123.3K

$170.9K

How much do senior data engineer jobs pay per year?

As of Jul 10, 2026, the average yearly pay for senior data engineer in Decatur, GA is $123,338.00, according to ZipRecruiter salary data. Most workers in this role earn between $103,500.00 and $140,600.00 per year, depending on experience, location, and employer.

What are Senior Data Engineers?

Senior Data Engineers are experienced professionals who design, build, and maintain large-scale data processing systems and infrastructure. They are responsible for developing data pipelines, managing databases, and ensuring the efficient flow and integrity of data across various platforms. Senior Data Engineers often collaborate with data scientists, analysts, and other engineers to support business intelligence and machine learning projects. They also play a key role in implementing best practices for data security, quality, and governance within an organization.

What is the difference between Senior Data Engineer vs Data Scientist?

AspectSenior Data EngineerData Scientist
Required CredentialsBachelor's/Master's in CS, Engineering, or related; experience with data pipelinesBachelor's/Master's in CS, Statistics, or related; proficiency in statistical analysis and modeling
Work EnvironmentBuild and maintain data infrastructure, optimize data workflowsAnalyze data, develop predictive models, generate insights
Employer & Industry UsageTech companies, finance, healthcare, where data engineering is essentialResearch, marketing, tech firms focusing on data analysis and modeling

While both roles work with data, Senior Data Engineers focus on developing and maintaining data infrastructure, whereas Data Scientists analyze data to generate insights and build models. They often collaborate but have distinct skill sets and responsibilities.

What are some common challenges Senior Data Engineers face when integrating data from multiple sources?

Senior Data Engineers often encounter challenges such as inconsistent data formats, varying data quality, and differing update frequencies when integrating data from multiple sources. Addressing these issues requires designing robust ETL (Extract, Transform, Load) pipelines, implementing data validation checks, and collaborating closely with source system owners to ensure data integrity. Effective communication with cross-functional teams and leveraging scalable data integration tools are also essential to streamline the process and minimize errors.

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

To thrive as a Senior Data Engineer, you need strong expertise in data modeling, ETL development, programming (such as Python or Scala), and a degree in computer science or a related field. Proficiency with big data technologies (like Hadoop, Spark), cloud platforms (AWS, Azure, GCP), and database systems, as well as relevant certifications, is highly valuable. Excellent problem-solving, communication, and leadership skills help you collaborate across teams and mentor junior engineers. These skills and qualities ensure robust, scalable data solutions that support organizational decision-making and growth.
What are the most commonly searched types of Data Engineer jobs in Decatur, GA? The most popular types of Data Engineer jobs in Decatur, GA are:
What are popular job titles related to Senior Data Engineer jobs in Decatur, GA? For Senior Data Engineer jobs in Decatur, GA, the most frequently searched job titles are:
What job categories do people searching Senior Data Engineer jobs in Decatur, GA look for? The top searched job categories for Senior Data Engineer jobs in Decatur, GA are:
What cities near Decatur, GA are hiring for Senior Data Engineer jobs? Cities near Decatur, GA with the most Senior Data Engineer job openings:
Senior Data Engineer jobs near you
Infographic showing various Senior Data Engineer job openings in Decatur, GA as of July 2026, with employment types broken down into 1% As Needed, 80% Full Time, 14% Part Time, 1% Temporary, and 4% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $123,338 per year, or $59.3 per hour.
Senior Data Engineer

Senior Data Engineer

Intercontinental Exchange Holdings, Inc.

Atlanta, GA • On-site

$101K - $138K/yr

Full-time

Re-posted 27 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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