Principal Data Engineer Jobs in Cumming, GA (NOW HIRING)

Aderant is a global industry leading software company providing comprehensive business management solutions for law firms and other professional services organizations with a mission to help them run a better business. We are motivated by a collective desire to drive the legal industry to the forefront of innovation. With over 2,500 clients around the world, including 95 of the top AmLaw 100 firms, we are changing the outside perception of the legal sphere; where there was once resistance to modernization, we are creating a culture that embraces new ideas and technology.

At Aderant, the "A" is more than just a letter. It is a representation of how we fulfill our foundational purpose, serving our clients. It embodies our core values and reminds us that to achieve success, every day must start with the "A". We bring the "A" to life by fostering a culture of innovation, collaboration, and personal growth. We encourage our diverse teams to bring their whole selves to work - ideas, experience, and passion - to drive our mission forward.

Our people are our strength.

Weare seeking a Principal Data Engineer to lead the design, development, and optimizationof our cloud-nativedata platform. Youwill be responsible for architecting scalable ETL pipelines, mentoring engineers, and drivingtechnical decisionsthat shapeourdata infrastructure. This isa hands-on leadershiprole requiring deep expertisein AWSdataservices, distributed computing, and moderndata lakehouse architectures.

• Architect and evolve our medallion-based datalakehouse(Bronze/Silver/Gold tiers) onAWS

• Design and implement data transformationpipelines thatscaletohandlepetabytesof data

• Establishbest practices for data modeling, includingdimensional modeling(Fact/Dimension tables) and slowlychanging dimensions

• Defineand enforcedata quality, governance, and security standards acrossthe platform

• Lead technicaldesignreviewsand provideguidanceon complex engineeringchallenges

• Build and maintain production-gradeETL pipelines using AWSGlue, PySpark, and ApacheIceberg

• Developreusable Pythonlibraries and frameworks for data processing and transformation

• Implement data lineage tracking and queryoptimizationstrategies

• Designevent-driven data architectures usingStepFunctions, Lambda, and SQS

• OptimizeSpark jobs for performance, costefficiency, and reliability

• Mentorand coachdataengineers, fostering a culture of technicalexcellence

• Partnerwith DataScientists, AnalyticsEngineers, and Productteamstounderstand datarequirements

• Collaborate with Platformand DevOps teams onCI/CD, observability, and infrastructureautomation

• Contributeto architectural decisions and technicalroadmap planning

• 8+ years of experienceindata engineering, with3+ years in aseniororlead capacity

• Proven trackrecord of designing and operatinglarge-scale data platforms inproduction

• Experienceleadingtechnicalprojectsand mentoring engineers

Proficiency withAWSdataengineeringservices including butnot limited to:

• DataMovement & Integration:DMS(Database Migration Service), SQS, Lambda

• Data Processing:AWSGlue, EMR, StepFunctions

• Data Storage:S3, DynamoDB, Redshift

• Governance& Observability:DataZone, CloudWatch, CloudTrail

• Expert-level proficiency in Python and SQL(Spark SQL, T-SQL, orsimilar)

• Deepexperiencewith ApacheSpark(PySpark) fordistributed data processing

• Strong knowledge of datalake tableformats: Apache Iceberg, DeltaLake, orApacheHudi

• Proficiency with dimensionalmodeling and data warehousedesignpatterns

• Experience with infrastructureas code and CI/CD pipelines(GitHub Actions, Terraform, orCloudFormation)

• Familiarity with data serialization formats(Parquet, Avro, JSON)

• Experiencedesigning medallion architectures orsimilartiered data processingpatterns

• Understandingof CDC (Change Data Capture) patterns and event-driven architectures

• Knowledgeof data lineage, cataloging, and metadata management

• Experienceimplementingrow-level security and dataaccesscontrols

• Experiencewith observability frameworkssuchas OpenTelemetry

• Familiarity with datavalidationlibraries(Pydantic, GreatExpectations)

• Experience with asyncPython(asyncio, aioboto3) for high-throughput applications

• Knowledge ofKubernetes and containerized workloads

• Experience with data meshordata productarchitectures

• Background in legal, financial, or enterpriseSaaS domains

Youwillwork with:

• Languages:Python, SQL, Spark SQL

• Compute:AWS Glue5.0, Lambda, Step Functions

• Storage:S3, DynamoDB, RedshiftServerless

• Formats:ApacheIceberg, Parquet, JSON

• Orchestration:AWS Step Functions, EventBridge

• CI/CD:GitHub Actions, multi-environment deployments

• Observability:CloudWatch, OpenTelemetry, custommetrics pipelines