Staff Data Engineer

The Hartford

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

Posted 9/24/2026full-timeUnited StatesLead💰 $135,040 - $202,560 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates extensive experience in building and optimizing data pipelines and products, with a strong focus on cloud technologies, big data methodologies, and data engineering best practices. Proficient in delivering end-to-end ELT solutions and implementing CI/CD capabilities aligned with Enterprise DevOps practices.

Highest-signal resume keywords

Data Engineering ExperienceCloud Technologies (AWS/Azure)Big Data Methodologies (AWS, Hadoop, Spark, Kafka, Snowflake)ETL Tools (PySpark, Informatica)CI/CD Implementation

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data Pipeline DevelopmentData Warehousing SolutionsSQL and NoSQLData Processing PipelinesData Mining AlgorithmsCloud Architecture DesignData Cleansing SolutionsTechnical DocumentationData MeshData Lake

Soft Skills

Problem SolvingCommunicationCollaboration

Tools & Technologies

SnowflakeOracleInformatica Cloud/PowerCenterGitHubQlikInformatica Mass IngestionSharePlexOpenFlowAWS EMRAWS S3

Certifications & Qualifications

AWS CertificationGCP CertificationSnowflake CertificationAI Foundation Certification

Industry Keywords

Data Engineering PracticesContinuous IntegrationContinuous DeliveryEnterprise DevOpsEmerging Data Technologies

Tech Stack

Tools & technologies

AWSAzureCloudDistributed SystemsETLGoogle Cloud PlatformHadoopInformaticaKafkaNoSQLOraclePySparkPythonSparkSQL

About the role

Key responsibilities & impact

Build small or medium-scale data pipelines and data products
Deliver end-to-end ELT solutions across multiple platforms and technologies
Influence solution architecture
Build and implement continuous integration and continuous delivery capabilities aligned with Enterprise DevOps practices
Influence pipeline tool decisions and support team development
Establish and follow data engineering practices for 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

Candidates 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
Hybrid work schedule
Perks & Benefits (listed by employer)