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Staff Data Engineer - Hybrid

The Hartford
USA
Full-time
Senior · 8+ years experience
USD 135040-202560 / year
Discovered 3 weeks ago
awsbedrockgcphadoopkafkapython

Full Job Posting

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/quality 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/POC, implement, and optimize Cloud/Hybrid architectures
  • Research, experiment, and utilize leading big data methodologies (AWS, Hadoop/EMR, Spark, Kafka, Snowflake) 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 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/AZURE), Python/Spark, Data mesh and Data Lake, Data Fabric
  • Must have hands on experience in Snowflake, Oracle, Informatica Cloud/Power 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/Python/snowflake native features
  • Must be familiar with AWS services such as EMR, S3, Lambda
  • Certifications on Cloud services such as AWS/GCP and Snowflake
  • Familiar with AI tools/tech 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:
  • The posted salary range reflects our ability to hire at different position titles and levels depending on background and experience.
  • Equal Opportunity Employer/Sex/Race/Color/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age
  • About Us | Our Culture | What It’s Like to Work Here | Perks & Benefits

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