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Thehartford

IND Staff Engineer, Data

LocationIndia GCC-Puppalaguda Village
Typefull-time
SeniorityLead
DepartmentEngineering
Company size10,000+ people
First seenOct 10, 2026 · 1d ago
Verified live1d ago
At a glanceSummarised by Seekless from the posting.
Must have6
Data engineering experience with demonstration of best practices in Programming, SDLC practices, Distributed systems
Developing and operating production workloads in cloud infrastructure
Focus on action and iterative deployment practices
Proven experience with software development life cycle (SDLC) and knowledge of agile/iterative methodologies and toolsets
Strong written and verbal communication skills
Ability to execute independently
Nice to have7
Tag management system experience, Tealium iQ preferred
Digital Analytics analysis and reporting tools experience - such as Google Analytics, Adobe Analytics and Tealium AudienceStream
ETL tools (Talend Studio, Informatica)
Reporting tools (Tableau, Data Studio)
Cloud Technologies (AWS, EMR, S3)
Data warehousing solutions (Snowflake, SnowSight, SQL)
An understanding of the practical application of DevSecOps and Agile methodologies
Skills
AWS
Hadoop
EMR
Spark
Kafka
Snowflake
Talend
Tealium iQ
Google Analytics
Adobe Analytics
Tealium AudienceStream
Talend Studio
Informatica
Tableau
Data Studio
S3
SnowSight
SQL
Python
SDLC
Agile
DevSecOps
DevOps
IND Staff Engineer - GCC091
About the company
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.
Responsibilities
Accountable for building small or medium scale pipeline and data products. Provides end-to-end solution delivery involving multiple platforms and technologies with small to medium complexity, leveraging ELT solutions to acquire, integrate, and operationalize data
Provides input to influence solution design
Build and implement capabilities for continuous integration  and continuous delivery aligned with Enterprise DevOps practices
Accountable for data engineering practices (e.g. Source code management, branching, issue tracking, access, etc.) followed for the product
Provide documentation and operating guidance for users of all levels. Document technical requirements and present technical concepts to audiences of varying size and level
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 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 technology-based decisions for tools and frameworks for effective delivery
Support the development and implementation of project and portfolio strategy, roadmaps and implementations
Requirements
Knowledge, Skills, and Abilities
Good working Technical Knowledge (Cloud data pipelines and data consumption products)
Ability to communicate at all levels within the digital analytics team and influence team leadership
Ability to work with cross-functional teams and translate requirements between business, project management and technical projects or programs
Team player with transformation mindset
Ability to operate successfully in a lean and fast-paced organization, leveraging Scaled Agile principles and ways of working
Must be able to collaborate across teams; demonstrate effective decision making, conflict resolution and relationship building
Ability to troubleshoot and resolve problems across the technology stack with guidance
Experience with data structures and services with APIs
Ability to collaborate with the team to mature code quality management, FinOps principles, automated testing, and environment management practices to deliver incremental customer value
Develops and promotes best practices for continuous improvement
Should have working knowledge and understanding of DevOps technology stack and standard tools/practices
Education, Experience, Certifications and Licenses
Minimum Qualifications:
Data engineering experience with demonstration of best practices in Programming, SDLC practices, Distributed systems
Developing and operating production workloads in cloud infrastructure
Focus on action and iterative deployment practices
Proven experience with software development life cycle (SDLC) and knowledge of agile/iterative methodologies and toolsets
Strong written and verbal communication skills
Ability to execute independently
Nice to have
Preferred Qualifications:
Tag management system experience, Tealium iQ preferred
Digital Analytics analysis and reporting tools experience - such as Google Analytics, Adobe Analytics and Tealium AudienceStream
ETL tools (Talend Studio, Informatica)
Reporting tools (Tableau, Data Studio)
Cloud Technologies (AWS, EMR, S3)
Data warehousing solutions (Snowflake, SnowSight, SQL)
An understanding of the practical application of DevSecOps and Agile methodologies
Certifications/Licenses (as applicable)
About Us | Our Culture | What It’s Like to Work Here
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