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⚙️Data Engineer

Senior Staff Data Engineer

Credit Karma · Bangalore, India
// classified as
Data Engineer (Pipelines, infra, ingestion, ETL.)
posted
1d ago
location
Bangalore, India
languages
java
tools
aws, kafka, neo4j
> stack
javaawskafkaneo4j
> description

Are you passionate about empowering people to test the impact of their ideas? Are you motivated by data-driven decisions? If 'yes', then the Intuit Experimentation Team (IXP) could be the right team for you.

The experimentation team builds and maintains the Intuit experimentation Platform, an enterprise-wide capability for moving rapidly and reliably from hypothesis to action. At Intuit, all teams (TurboTax, QuickBooks, CreditKarma and MailChimp to name a few) use IXP. Our aim is to give every individual at Intuit a voice by providing them a platform where they can test their ideas and have data from their experiments backing their ideas.

 

We have:

 

  • An opportunity for you to influence the experimentation program at Intuit.

  • An opportunity for you to enable innovation across Intuit with your contributions to the experimentation platform

  • An opportunity to work with the latest technology and frameworks.

  • An opportunity to work with a collaborative, customer-obsessed, and diverse engineering team.


Responsibilities


  • Drive significant technology initiatives end-to-end and across multiple layers of architecture.

  • Drive design and implementation of durable and software solutions that will solve critical customer problems, are scalable, secure, easy to maintain, and interact with numerous other

  • Provide technical leadership and be a role model/coach to software engineers pursuing technical career path in engineering

  • Provide/inspire innovations that fuel the growth of Intuit as a whole and generate creative ideas for emerging business needs

  • Actively stay abreast on industry best practices, share learnings, and experiment and apply cutting edge technologies


Qualifications


  • BS/MS in Computer Science or related area or equivalent experience 

  • 10+ years of professional experience designing and developing distributed scalable and highly reliable enterprise applications in Cloud.  

  • 7+ years of experience in Back-end technologies like Java, Spring, Express (NodeJS)

  • 7+ years of experience designing and operating high-throughput, low-latency distributed systems that process data at petabyte scale

  • 5+ years of experience with Streaming applications using Kafka, Apache Beam, Flink

  • Full-stack development experience with AI technologies/tools and apply it to user experiences or backend solutions.

  • Ability to navigate multi-layered environments and mobilize various stakeholders to deliver results at pace.

  • Experience with AWS or equivalent services is preferred. 

  • Expert at distilling complex technical concepts into persuasive narratives for stakeholders at all levels, including executive leadership.

  • Proven ability to drive results across global, decentralized teams by fostering collaboration and maintaining strong professional relationships across time zones.

  • Combines sharp analytical skills with a 'self-starter' mindset to navigate and thrive within fast-paced, technical ecosystems.

  • Knowledge of AI/ML and GenAI technologies — LLMs, RAG, Semantic Search (e.g Vertex AI search, AWS cloud search) and Knowledge Graph (e.g neo4j, ..) to integrate our data with generative AI experiences

  • Track record of mentoring engineers and driving technical alignment across teams through design documents and architecture reviews


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Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position may be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at Intuit®: Careers | Benefits). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender.