IND Staff Engineer, Data

The Hartford; India; On-site; INR 2,400,000 - 3,600,000; Full time

Job summary

The Hartford in India is seeking an IND Staff Engineer to design and implement cloud-based data pipelines and analytics data products. You will contribute to end-to-end delivery across platforms, align with DevOps practices, and help mature data engineering standards and tooling.

You will collaborate with cross-functional teams to translate business requirements into scalable data solutions, stay current with modern data technologies, and ensure robust, maintainable systems in a lean, fast-paced

Qualifications

• Experience with building production-grade data pipelines
• Strong understanding of SDLC and Agile methodologies
• Ability to collaborate with cross-functional teams
• Familiarity with cloud-based data platforms (AWS) and on-premise hybrids
• Excellent problem-solving and communication skills

Responsibilities

• Build small to medium-scale data pipelines and data products
• Deliver end-to-end solutions across platforms and tech stacks
• Implement CI/CD and DevOps practices for data projects
• Document requirements and provide operating guidance for users
• Stay updated on emerging data analytics technologies and best practices

Skills

Cloud data pipelines

ELT

Big data

AWS

Hadoop/EMR

Spark

Kafka

Snowflake

Talend

CI/CD

DevOps practices

SDLC

Agile

Communication

Education

Bachelor’s degree in Computer Science or equivalent

Data engineering certification

Tools

Talend Studio

Informatica

Tableau / Data Studio

Snowflake

Spark

Job description

IND Staff Engineer - GCC091We’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 dataProvides input to influence solution designBuild and implement capabilities for continuous integration and continuous delivery aligned with Enterprise DevOps practicesAccountable for data engineering practices (e.g. Source code management, branching, issue tracking, access, etc.) followed for the productProvide documentation and operating guidance for users of all levels. Document technical requirements and present technical concepts to audiences of varying size and levelResearch, 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 levelImplement, 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 deliverySupport the development and implementation of project and portfolio strategy, roadmaps and implementations Knowledge, Skills, and AbilitiesGood working Technical Knowledge (Cloud data pipelines and data consumption products)Ability to communicate at all levels within the digital analytics team and influence team leadershipAbility to work with cross-functional teams and translate requirements between business, project management and technical projects or programsTeam player with transformation mindsetAbility to operate successfully in a lean and fast-paced organization, leveraging Scaled Agile principles and ways of workingMust be able to collaborate across teams; demonstrate effective decision making, conflict resolution and relationship buildingAbility to troubleshoot and resolve problems across the technology stack with guidanceExperience with data structures and services with APIsAbility to collaborate with the team to mature code quality management, FinOps principles, automated testing, and environment management practices to deliver incremental customer valueDevelops and promotes best practices for continuous improvementShould have working knowledge and understanding of DevOps technology stack and standard tools/practices Education, Experience, Certifications and LicensesMinimum Qualifications: Data engineering experience with demonstration of best practices in Programming, SDLC practices, Distributed systemsDeveloping and operating production workloads in cloud infrastructureFocus on action and iterative deployment practicesProven experience with software development life cycle (SDLC) and knowledge of agile/iterative methodologies and toolsetsStrong written and verbal communication skillsAbility to execute independentlyPreferred Qualifications: Tag management system experience, Tealium iQ preferredDigital Analytics analysis and reporting tools experience - such as Google Analytics, Adobe Analytics and Tealium AudienceStreamETL 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 methodologiesCertifications/Licenses (as applicable)