Workday

Full Stack Sr Data Engineer

Remote Pune, India
Machine Learning Microservices gRPC Python SQL Deep Learning Git
Description

Your work days are brighter here.

At Workday, it all began with a conversation over breakfast. When our founders met at a sunny California diner, they came up with an idea to revolutionize the enterprise software market. And when we began to rise, one thing that really set us apart was our culture. A culture which was driven by our value of putting our people first. And ever since, the happiness, development, and contribution of every Workmate is central to who we are. Our Workmates believe a healthy employee-centric, collaborative culture is the essential mix of ingredients for success in business. That’s why we look after our people, communities and the planet while still being profitable. Feel encouraged to shine, however that manifests: you don’t need to hide who you are. You can feel the energy and the passion, it's what makes us unique. Inspired to make a brighter work day for all and transform with us to the next stage of our growth journey? Bring your brightest version of you and have a brighter work day here.

At Workday, we value our candidates’ privacy and data security.  Workday will never ask candidates to apply to jobs through websites that are not Workday Careers. 

  

Please be aware of sites that may ask for you to input your data in connection with a job posting that appears to be from Workday but is not.

  

In addition, Workday will never ask candidates to pay a recruiting fee, or pay for consulting or coaching services, in order to apply for a job at Workday.

About the Team

Ignite your passion for innovation and transform finance with Workday's Finance AI (FinAI) Innovation Center team.

Join our team of data science (DS) and machine learning (ML) experts where we do more than build algorithms. We empower finance professionals to achieve remarkable things. We automate mundane tasks, freeing them to focus on high-impact activities. We unlock hidden patterns and deliver actionable insights that lead to improved financial forecasting, optimized resource allocation, business process improvements, and significant cost reductions.

Work alongside passionate experts who share your drive to make a tangible difference. Develop your skills in a rapidly evolving field while bridging the gap between technical and non-technical partners, ensuring everyone understands the transformative power of AI.

This is more than just a job; it's an opportunity to be part of something truly special. Join us and become an architect of the future for finance.

About the Role

We are searching for a result focused and innovative individual to orchestrate the design, implementation, and management of our machine learning-focused finance data lake. This critical role involves steering our technical data engineering strategy and driving AI initiatives to expedite finance digitization and transformation. Your responsibilities include supporting ML use cases throughout a project's life cycle – from ad-hoc exploration to preparing training data, feature engineering, building scalable fault-tolerant data pipelines, and ensuring robust production deployment. As the ideal candidate, you thrive on collaboration, closely partnering with business, data science, machine learning, and analytics teams to gather requirements and propel continuous development of the data lake. Join us in shaping the future of our organization's data-driven success.

Responsibilities:

  • Work on developing cutting-edge data science and engineering solutions to help shape and drive business innovation.

  • Ability to think outside the box and look for opportunities where ML or AI can solve problems in new and innovative ways.

  • Build a robust and scalable data architecture capable of handling large data volumes.

  • Analyze complex data requirements and design data models that meet organizational needs.

  • Design and be the lead developer on data pipelines to process and transform raw data efficiently from various sources.

  • Implement backend microservices for large scale distributed systems using gRPC or REST.

  • Apply data integration, validation and transformation techniques to ensure data quality and consistency.

  • Optimize data processing pipelines and implement performance tuning techniques.

  • Ensure the security and privacy of data by implementing access controls, encryption mechanisms, and data anonymization techniques.

  • Establish monitoring and auditing mechanisms to proactively identify and rectify any data issues ensuring a high level of data integrity.

  • Create and maintain visualization dashboards and reports for actionable insights.

  • Work in an Agile environment focused on collaboration and teamwork.

  • Develop roadmaps and requirements, identify risks, and develop contingency plans.

  • Communicate project status to relevant partners.

About You

  • 8+ years of professional experience in data engineering, software development, or MLOps involving large-scale, real-time cloud based distributed systems.

  • Bachelor's degree in Computer Science (or related field) or equivalent work experience.

  • Strong foundation in data engineering concepts, including data modeling, database design, ETL (Extract, Transform, Load) processes, and data warehousing.

  • Proficiency in Python, SQL, and PySpark, with a focus on applying these to data engineering tasks.

  • Familiarity with various machine learning models like regression, classification, clustering, deep learning, etc

  • Knowledge of tools like Git, MLflow, DVC (Data Version Control), or Weights & Biases for tracking experiments and model versions.

  • Proficiency with technologies like SnowFlake and Databricks.

  • Expertise with data visualization tools like Tableau, Power BI, Sigma or similar. 

  • Familiarity with code repository and project tools such as GitHub, JIRA, and Confluence.

  • Strong communication ability to liaise with various partners, including data scientists, business analysts, and executives, to understand requirements and translate them into technical solutions.



Our Approach to Flexible Work
 

With Flex Work, we’re combining the best of both worlds: in-person time and remote. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. We know that flexibility can take shape in many ways, so rather than a number of required days in-office each week, we simply spend at least half (50%) of our time each quarter in the office or in the field with our customers, prospects, and partners (depending on role). This means you'll have the freedom to create a flexible schedule that caters to your business, team, and personal needs, while being intentional to make the most of time spent together. Those in our remote "home office" roles also have the opportunity to come together in our offices for important moments that matter.

Are you being referred to one of our roles? If so, ask your connection at Workday about our Employee Referral process!

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