Staff Data Engineer

The Hartford

. Build small- or medium-scale pipelines and data products .

Posted 9/21/2026full-timeUnited StatesLead💰 $135,040 - $202,560 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates extensive experience in data engineering, focusing on building and optimizing data pipelines and products using cloud technologies like AWS and Snowflake. Proficient in implementing CI/CD practices and leveraging big data methodologies to deliver end-to-end solutions.

Highest-signal resume keywords

Data Engineering ExperienceCloud Technologies (AWS/Azure)CI/CD ImplementationBig Data MethodologiesSnowflake Proficiency

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data Pipeline DevelopmentSQLNoSQLETL ToolsPythonSparkData WarehousingData MeshData LakeData Fabric

Soft Skills

Documentation SkillsProblem-Solving

Tools & Technologies

AWS EMRSnowflakeOracleInformatica Cloud/PowerCenterGitHubQlikInformatica Mass IngestionSharePlexOpenFlowDMS

Certifications & Qualifications

AWS CertificationGCP CertificationSnowflake CertificationAI Foundation Certification

Industry Keywords

Data Engineering Best PracticesDistributed SystemsContinuous IntegrationContinuous DeliveryData Quality Solutions

Tech Stack

Tools & technologies

AWSAzureCloudDistributed SystemsETLGoogle Cloud PlatformHadoopInformaticaKafkaNoSQLOraclePySparkPythonSparkSQL

About the role

Key responsibilities & impact

Build small- or medium-scale pipelines and data products
Deliver end-to-end solutions across multiple platforms and technologies
Leverage ELT solutions to acquire, integrate, and operationalize data
Provide significant input into solution architecture
Build and implement continuous integration and continuous delivery capabilities aligned with Enterprise DevOps practices
Influence pipeline tool decisions and support team development
Ensure data engineering practices are followed for data pipelines
Review, prepare, design, and integrate complex data; correct problems and recommend data cleansing and quality solutions
Provide expert documentation and operating guidance
Document technical requirements and present complex technical concepts to varied audiences
Architect, design, prototype, implement, and optimize cloud/hybrid architectures
Research and use big data methodologies including AWS, Hadoop/EMR, Spark, Kafka, and Snowflake
Implement and test data processing pipelines and data mining/data science algorithms
Stay current on emerging data and analytics technologies, tools, techniques, and frameworks
Evaluate and recommend technology tools and frameworks
Support project and portfolio strategy, roadmaps, and implementation

Requirements

What you’ll need

Must be authorized to work in the US without company sponsorship
The company will not support the STEM OPT I-983 Training Plan endorsement for this position
8+ years of data engineering experience and best practices in distributed systems, data warehousing solutions, SQL and NoSQL, ETL tools, CI/CD, big data, cloud technologies (AWS/Azure), Python/Spark, data mesh, data lake, and data fabric
Hands-on experience with Snowflake, Oracle, Informatica Cloud/PowerCenter, and GitHub
Hands-on experience and knowledge of replication tools such as Qlik, Informatica Mass Ingestion, SharePlex, OpenFlow, and DMS
Familiarity with ETL using PySpark, Python, and Snowflake native features
Familiarity with AWS services such as EMR, S3, and Lambda
Certifications on cloud services such as AWS/GCP and Snowflake
Familiarity with AI tools/tech stack
Nice to have: Certifications on AI foundation
Nice to have: Hands-on experience with AWS Bedrock and Google Vertex

Benefits

Comp & perks

Short-term or annual bonuses
Long-term incentives
On-the-spot recognition
Perks & Benefits (details not specified)