Staff Data Engineer - Hybrid

tunities 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 engineer practices (e.g. Source code management, branching, issue tracking, access, etc.) followed for the product

• Independently review, prepare, design and integrate complex (type, quality, volume) data, correcting problems and recommend data cleansing/quality solutions to issues

• 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/POC, implement, and optimize Cloud/Hybrid architectures

• Research, experiment, and utilize leading big data methodologies (AWS, Hadoop/EMR, Spark, Kafka, Snowflake and Talend) with cloud/on premise hybrid hosting solutions, on a project level

• Implement, and test data processing pipelines, and data mining/data 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, recommend, and

• influence 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.

• 5+ years of data engineering experience and best practices in Distributed systems, Data warehousing solutions SQL and NoSQL, ETL tools, CICD, Bigdata, Cloud Technologies (AWS/AZURE),Python/Spark, Data mesh and Data Lake, Data Fabric

• Must have Snowflake and IDMC/ Informatica experience

• 2+ years of developing and operating production workloads in cloud infrastructure

• knowledge of agile/iterative methodologies and toolsets

• Ability to execute independently

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/Sex/Race/Color/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age