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Co","hartford-fire-ins-co",false,true,{"@context":14,"@type":15,"title":6,"description":16,"hiringOrganization":17,"datePosted":19,"validThrough":20,"jobLocation":21,"jobLocationType":33,"employmentType":34,"industry":36,"skills":38,"baseSalary":88},"https:\u002F\u002Fschema.org\u002F","JobPosting","Staff Data Engineer - GE07CE We’re determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working here means having every opportunity to achieve your goals – and to help others accomplish theirs, too. Join our team as we help shape the future. As a Senior Staff Data Engineer supporting Employee Benefits Sales, you will play a key role in shaping how Sales and Underwriting data is ingested, transformed, and delivered across the organization. You’ll work on modern, cloud‑based data platforms to ensure high‑quality, governed data products that drive operational efficiency, analytics, and decision‑making. This role combines deep technical expertise with strong partnership across Underwriting, Product and Enterprise Data teams. The position offers a strong growth path toward Technical Leadership, with hands-on ownership of Quote and Underwriting data pipelines and opportunities to mentor and influence across teams. This role will have a Hybrid work schedule, with the expectation of working in an office location (Hartford, CT; Chicago, IL; Columbus, OH; and Charlotte, NC) 3 days a week (Tuesday through Thursday). Responsibilities: Accountable for building small or medium-scale pipelines and data products. End-to-End solution delivery involving multiple platforms and technologies with small to medium complexity or certain sub-systems of large, complex implementations, leveraging ELT solutions to acquire, integrate, and operationalize data Provides significant input to influence solution architecture Build and implement capabilities for continuous integration and continuous delivery aligned with Enterprise DevOps practices. Accountable for team development and influencing pipeline tool decisions Accountable for data engineering practices (e.g. Source code management, branching, issue tracking, access, etc.) to be followed for the data pipeline Independently review, prepare, design and integrate complex (type, quality, volume) data, correcting problems and recommend data cleansing\u002Fquality solutions Provide expert documentation and operating guidance for users of all levels. Document technical requirements and present complex technical concepts to audiences of varying sizes and levels. Rapidly architect, design, prototype\u002FPOC, implement, and optimize Cloud\u002FHybrid architectures Research, experiment, and utilize leading big data methodologies (AWS, Hadoop\u002FEMR, Spark, Kafka, Snowflake) with cloud\u002Fon premise hybrid hosting solutions, on a project level Implement, and test data processing pipelines, and data mining\u002Fdata science algorithms on a variety of hosted settings (AWS,Client technology stacks) Stay up to date on emerging data and analytics technologies, tools, techniques, and frameworks. Evaluate and recommend all technology-based decisions for tools and frameworks for effective delivery Support the development and implementation of project and portfolio strategy, roadmaps and implementation Qualifications: 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, CICD, Bigdata, Cloud Technologies (AWS\u002FAZURE), Python\u002FSpark, Data mesh and Data Lake, Data Fabric Must have hands on experience in Snowflake, Oracle, Informatica Cloud\u002FPower center, Github Must have hands-on experience and knowledge on replication tools like Qlik, Informatica mass ingestion, Shareplex, open flow, DMS Must be familiar with ETL using Pyspark\u002FPython\u002Fsnowflake native features Must be familiar with AWS services such as EMR, S3, Lambda Certifications on Cloud services such as AWS\u002FGCP and Snowflake Familiar with AI tools\u002Ftech stack Nice to have qualifications: Certifications on AI foundation Hands-on experience with AWS Bedrock and Google Vertex Compensation The listed annualized base pay range is primarily based on analysis of similar positions in the external market. Actual base pay could vary and may be above or below the listed range based on factors including but not limited to performance, proficiency and demonstration of competencies required for the role. The base pay is just one component of The Hartford’s total compensation package for employees. Other rewards may include short-term or annual bonuses, long-term incentives, and on-the-spot recognition. The annualized base pay range for this role is: $125,760 - $188,640 Equal Opportunity Employer\u002FSex\u002FRace\u002FColor\u002FVeterans\u002FDisability\u002FSexual Orientation\u002FGender Identity or Expression\u002FReligion\u002FAge About Us | Our Culture | What It’s Like to Work Here | Perks & Benefits Every day, a day to do right. Showing up for people isn’t just what we do. It’s who we are – and have been for more than 200 years. We’re devoted to finding innovative ways to serve our customers, communities and employees—continually asking ourselves what more we can do. Is our policy language as simple and inclusive as it can be? Can we better help businesses navigate our ever-changing world? What else can we do to destigmatize mental health in the workplace? Can we make our communities more equitable? That we can rise to the challenge of these questions is due in no small part to our company values that our employees have shaped and defined. And while how we contribute looks different for each of us, it’s these values that drive all of us to do more and to do better every day. About Us Our Culture What It’s Like to Work Here Perks & Benefits Legal Notice Accessibility Statement Producer Compensation EEO Privacy Policy California Privacy Policy Your California Privacy Choices International Privacy Policy Canadian Privacy Policy Unincorporated Areas of LA County, CA (Applicant Information) MA Applicant Notice Hartford India Prospective Personnel Privacy Notice Electronic Monitoring Policy",{"@type":18,"name":9},"Organization","2026-10-09","2027-10-09",[22],{"@type":23,"address":24,"geo":29},"Place",{"@type":25,"addressLocality":26,"addressCountry":27,"addressRegion":28},"PostalAddress","Hartford","US","Connecticut",{"@type":30,"latitude":31,"longitude":32},"GeoCoordinates",41.7658043,-72.6733723,"HYBRID",[35],"PERMANENT",[37],"Insurance",[39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87],"SQL","NoSQL","ETL","CI\u002FCD","Big Data","AWS","Azure","Python","Spark","Snowflake","Oracle","Informatica Cloud","Informatica PowerCenter","GitHub","Qlik","Shareplex","OpenFlow","AWS DMS","PySpark","AWS EMR","AWS S3","AWS Lambda","AI Tools","AWS Bedrock","Google Vertex","Partnership","Mentoring","Influence","Documentation","Presentation","Team Development","Data Engineering","Distributed Systems","Data Warehousing","Data Mesh","Data Lake","Data Fabric","Solution Architecture","Data Cleansing","Data Quality","Technical Requirements Documentation","Cloud Architecture","Big Data Methodologies","Data Processing Pipelines","Data Mining","Data Science Algorithms","Project Strategy","Portfolio Strategy","Roadmaps",{"@type":89,"currency":90,"value":91},"MonetaryAmount","USD",{"@type":92,"minValue":93,"maxValue":94,"unitText":95},"QuantitativeValue",125760,188640,"YEAR",[31],[32],"permanent",[100],"FULL_TIME",[100],"hybrid","estimated",[105,106,107],"Short-term or annual bonuses","Long-term incentives","On-the-spot recognition",[105,106,107],"insurance",[],[112],"Hartford, Connecticut, USA",[],[26],[],[117],"USA",[27],"# Staff Data Engineer - GE07CE\n\nWe’re determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working here means having every opportunity to achieve your goals – and to help others accomplish theirs, too. Join our team as we help shape the future.\n\nAs a Senior Staff Data Engineer supporting Employee Benefits Sales, you will play a key role in shaping how Sales and Underwriting data is ingested, transformed, and delivered across the organization. You’ll work on modern, cloud‑based data platforms to ensure high‑quality, governed data products that drive operational efficiency, analytics, and decision‑making. This role combines deep technical expertise with strong partnership across Underwriting, Product and Enterprise Data teams. The position offers a strong growth path toward Technical Leadership, with hands-on ownership of Quote and Underwriting data pipelines and opportunities to mentor and influence across teams.\n\nThis role will have a Hybrid work schedule, with the expectation of working in an office location (Hartford, CT; Chicago, IL; Columbus, OH; and Charlotte, NC) 3 days a week (Tuesday through Thursday).\n\n## Responsibilities:\n\n- Accountable for building small or medium-scale pipelines and data products.\n- End-to-End solution delivery involving multiple platforms and technologies with small to medium complexity or certain sub-systems of large, complex implementations, leveraging ELT solutions to acquire, integrate, and operationalize data\n- Provides significant input to influence solution architecture\n- Build and implement capabilities for continuous integration and continuous delivery aligned with Enterprise DevOps practices.\n- Accountable for team development and influencing pipeline tool decisions\n- Accountable for data engineering practices (e.g. Source code management, branching, issue tracking, access, etc.) to be followed for the data pipeline\n- Independently review, prepare, design and integrate complex (type, quality, volume) data, correcting problems and recommend data cleansing\u002Fquality solutions\n- Provide expert documentation and operating guidance for users of all levels.\n- Document technical requirements and present complex technical concepts to audiences of varying sizes and levels.\n- Rapidly architect, design, prototype\u002FPOC, implement, and optimize Cloud\u002FHybrid architectures\n- Research, experiment, and utilize leading big data methodologies (AWS, Hadoop\u002FEMR, Spark, Kafka, Snowflake) with cloud\u002Fon premise hybrid hosting solutions, on a project level\n- Implement, and test data processing pipelines, and data mining\u002Fdata science algorithms on a variety of hosted settings (AWS,Client technology stacks)\n- Stay up to date on emerging data and analytics technologies, tools, techniques, and frameworks.\n- Evaluate and recommend all technology-based decisions for tools and frameworks for effective delivery\n- Support the development and implementation of project and portfolio strategy, roadmaps and implementation\n\n## Qualifications:\n\n- 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.\n- 8+ years of data engineering experience and best practices in Distributed systems, Data warehousing solutions SQL and NoSQL, ETL tools, CICD, Bigdata, Cloud Technologies (AWS\u002FAZURE), Python\u002FSpark, Data mesh and Data Lake, Data Fabric\n- Must have hands on experience in Snowflake, Oracle, Informatica Cloud\u002FPower center, Github\n- Must have hands-on experience and knowledge on replication tools like Qlik, Informatica mass ingestion, Shareplex, open flow, DMS\n- Must be familiar with ETL using Pyspark\u002FPython\u002Fsnowflake native features\n- Must be familiar with AWS services such as EMR, S3, Lambda\n- Certifications on Cloud services such as AWS\u002FGCP and Snowflake\n- Familiar with AI tools\u002Ftech stack\n\n## Nice to have qualifications:\n\n- Certifications on AI foundation\n- Hands-on experience with AWS Bedrock and Google Vertex\n\n## Compensation\n\nThe listed annualized base pay range is primarily based on analysis of similar positions in the external market. Actual base pay could vary and may be above or below the listed range based on factors including but not limited to performance, proficiency and demonstration of competencies required for the role. The base pay is just one component of The Hartford’s total compensation package for employees. Other rewards may include short-term or annual bonuses, long-term incentives, and on-the-spot recognition. The annualized base pay range for this role is: $125,760 - $188,640\n\nEqual Opportunity Employer\u002FSex\u002FRace\u002FColor\u002FVeterans\u002FDisability\u002FSexual Orientation\u002FGender Identity or Expression\u002FReligion\u002FAge\n\nAbout Us | Our Culture | What It’s Like to Work Here | Perks & Benefits\n\nEvery day, a day to do right. Showing up for people isn’t just what we do. It’s who we are – and have been for more than 200 years. We’re devoted to finding innovative ways to serve our customers, communities and employees—continually asking ourselves what more we can do. Is our policy language as simple and inclusive as it can be? Can we better help businesses navigate our ever-changing world? What else can we do to destigmatize mental health in the workplace? Can we make our communities more equitable? That we can rise to the challenge of these questions is due in no small part to our company values that our employees have shaped and defined. And while how we contribute looks different for each of us, it’s these values that drive all of us to do more and to do better every day.\n\nAbout Us\nOur Culture\nWhat It’s Like to Work Here\nPerks & Benefits\nLegal Notice\nAccessibility Statement\nProducer Compensation\nEEO\nPrivacy Policy\nCalifornia Privacy Policy\nYour California Privacy Choices\nInternational Privacy Policy\nCanadian Privacy Policy\nUnincorporated Areas of LA County, CA (Applicant Information)\nMA Applicant Notice\nHartford India Prospective Personnel Privacy Notice\nElectronic Monitoring Policy",{"aws":121,"etl":121,"sql":121,"qlik":122,"azure":122,"ci\u002Fcd":122,"nosql":122,"spark":121,"aws s3":122,"github":122,"oracle":122,"python":121,"aws dms":122,"aws emr":122,"pyspark":121,"ai tools":123,"big data":121,"openflow":122,"shareplex":122,"snowflake":121,"aws lambda":122,"aws bedrock":123,"google vertex":123,"informatica cloud":122,"informatica powercenter":122},4,3,2,[39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63],{"partnership":121,"mentoring":121,"influence":121,"documentation":121,"presentation":121,"team development":121},[64,65,66,67,68,69],{"roadmaps":122,"data lake":122,"data mesh":122,"data fabric":122,"data mining":122,"data quality":121,"data cleansing":121,"data engineering":121,"data warehousing":121,"project strategy":122,"cloud architecture":121,"portfolio strategy":122,"distributed systems":121,"solution architecture":121,"big data methodologies":121,"data science algorithms":122,"data processing pipelines":121,"technical requirements documentation":121},[70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87],{"detected_language_jobad":130,"required":131},"en",[132],[133],{"language":134,"level":135},"ENGLISH","C1",8,[138,139],"Software and Applications Development and Analysis","Database and Network Professionals",[138,139],"https:\u002F\u002Fthehartford.wd5.myworkdayjobs.com\u002Fen-us\u002Fcareers_external\u002Fjob\u002Fhartford-ct\u002Fstaff-data-engineer---hybrid_r2627202",1]