IND Staff Data Engineer

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:

• 6 to 9 years of software development or data engineering experience with demonstration of best practices in Programming, SDLC practices, Distributed systems

• 1+ years of 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)