Manager, Data Engineering

Manager, Data Engineering Manager, Data Engineering Manager, Data Engineering Req ID FY|S&M|#3 Location(s) Bangalore, India; Work arrangement(s) Hybrid (works from home and New Relic office throughout the week) Your opportunity Do you love the transformative impact data can have on a business? Are you motivated to push for results and overcome all obstacles? Then we have a role for you. At New Relic, data engineering teams build data products for analytics, billing and research. We need a hands on data engineering manager who brings passion for data quality, code quality, and SLAs. Someone with the vision to imagine what a future state should be and the drive to make it happen. You will enable a cross-functional team of engineers to create best-in-class data products, while maintaining our evolving environment. What you'll do

• Proactively drive the vision for BI and Enterprise Data Warehousing across a product vertical, and define and execute on a plan to achieve that vision.
• Lead a team of highly qualified and experienced data engineers and grow the team through active mentorship and other growth opportunities
• Lead the building of scalable, fault tolerant pipelines with built in data quality checks that transform, load and curate data from various internal and external systems
• Provide leadership to cross-functional initiatives and projects.
• Influence architecture design and decisions.
• Build cross-functional relationships with Data Scientists, Product Managers and Software Engineers to understand data needs and deliver on those needs.
• Improve engineering processes and cross-team collaboration.
• Ruthlessly prioritize work to align with company priorities.
• Provide thought leadership to grow and evolve DE function and implementation of SDLC best practices in building internal-facing data products by staying up-to-date with industry trends, emerging technologies, and best practices in data engineering
• Minimum 4 years of experience with dbt, Airflow and snowflake
• Experience with Apache Iceberg tables
• Experience and knowledge of building data-lakes in AWS Spark / Glue, Athena), including data modeling, data quality best practices, and self-service tooling.
• Experience mentoring data professionals from junior to senior levels
• Demonstrated success leading cross functional initiatives
• Passionate about data quality, code quality, SLAs and continuous improvement
• Deep understanding of data system architecture
• Deep understanding of ETL / ELT patterns

This role requires

Bonus points if you have

Fostering a diverse, welcoming and inclusive environment is important to us. We work hard to make everyone feel comfortable bringing their best, most authentic selves to work every day. We celebrate our talented Relics’ different backgrounds and abilities, and recognize the different paths they took to reach us – including nontraditional ones. Their experiences and perspectives inspire us to make our products and company the best they can be. We’re looking for people who feel connected to our mission and values, not just candidates who check off all the boxes.

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Our hiring process

Please note that visa sponsorship is not available for this position.

In compliance with applicable law, all persons hired will be required to verify identity and eligibility to work and to complete employment eligibility verification. Note : Our stewardship of the data of thousands of customers’ means that a criminal background check is required to join New Relic.

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New Relic is proud to be an equal opportunity employer. We foster a diverse, equitable, and inclusive environment, free from all types of discrimination, so our Relics can thrive. We hire people with different backgrounds, experiences, abilities and perspectives.

Candidates are evaluated based on qualifications, regardless of race, religion, ethnicity, national origin, sex, sexual orientation, gender expression or identity, age, disability, neurodiversity, veteran or marital status, political viewpoint, or other legally protected characteristics.

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