IND Staff Engineer, Data

The Hartford India; Hyderabad; On-site; INR 1,800,000 - 3,000,000; Full time

Job summary

The Hartford India seeks an IND Staff Engineer to design and implement scalable data pipelines and analytics products in a hybrid cloud environment. You will own end-to-end delivery across AWS-based and on-premise components, drive CI/CD practices, and collaborate with cross‑functional teams to translate business needs into robust data solutions.

Responsibilities include building data processing pipelines, mentoring teammates, evaluating new technologies, and contributing to portfolio strategy

Qualifications

• Experience building data pipelines and data products.
• Proven SDLC experience with agile/iterative methodologies.
• Cloud infrastructure experience (AWS) and on-premise hybrid hosting.

Responsibilities

• Build data processing pipelines and data mining across hosted settings.
• Implement and test CI/CD for data platforms with DevOps practices.
• Provide documentation and guidance for users at all levels.

Skills

Cloud data pipelines

Cross-functional collaboration

Scaled Agile

DevOps practices

APIs and data services

Education

Data engineering in cloud

SDLC and Agile

Tools

Talend Studio

Informatica

Tableau/Data Studio

Snowflake

AWS EMR

Job description

IND Staff Engineer - GCC091

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.

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

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

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)