Lead Data Engineer
Hyderabad, TG, IN
About the role
Are you sharp, ambitious, and looking for an exciting challenge where you can help us move towards our target architecture? We have many critically important data processing pipelines to build and a data architecture to evolve. Do you want to learn from an amazing international team, where you can grow your technical expertise and functional acumen, and where you can make a difference? If yes, then read on.
This is a superb role in our Finance InfoTech Data & Analytics product area, where you will be focusing on software/data engineering mostly using Python alongside cloudnative technologies (Databricks, Azure DevOps, delta lake tables, spark structured streaming, lakehouse architecture) in Microsoft Azure. We process billions of records of financial data, constantly pushing forward the limits of our system and seeking for better scalability, lower end-to-end processing latency, and improved processing transparency.
In this expert level role, you will be both an individual contributor and a mentor to other engineers. You will participate fully in the development lifecycle, not only engineering and maintaining high-stability and performant solutions, but also working closely with our business partners, IT experts and architects to help understand requirements, shape and evaluate solutions, participating in code reviews, ensuring accurate and relevant documentation and not least of all, supporting our operations team with complex problems.
About the team
- The role is in the Integration team of the Data & Analytics Product Area which is developing and operating state of the art integrations at the Finance Division of Swiss Re.
- The integration team is globally distributed with the Produce Owner based in Bangalore and focuses on building and operating the future of integration for Finance as Swiss Re.
- The team builds on a lakehouse architecture using Azure Databricks, Azure Data Factory and Azure Data Lake (Delta Lake) with Python being the main programming language and PySpark are used for large scale data engineering.
About You
You are a result-driven experienced software engineer, passionate about your craft and eager to grow further, comfortable meeting (sometimes tight) deadlines and confidently taking ownership of features. You have an accomplished record in delivering sustainable solutions and you desire to develop your skills and knowledge about the platforms which you will be working on, both the technical aspects and how they are used by our business partners. You are comfortable working in multi-dimensional agile teams with direct involvement from business subject matter experts and care about security, quality, user experience, documentation, testing, team spirit and the overall big picture. Finally, you want to put clean code principles into practice on large code bases.
Your core assets:
- Bachelor's or master's degree in computer science, or any other related field
- Strong software engineering skills, including familiarity and application of design patterns, and engineering best practices.
- Proven experience developing complex software systems as a software engineer (at least 5 years)
- Strong understanding of data engineering techniques with high level programming languages (e.g., Java, C#, or Python) and analytical frameworks
- Strong core Python software engineering experience
- At least 3 years for hands on experience with Apache Spark (PySpark), developing applications using an IDE such as VS Code or PyCharm
- Experience of working with delta lakes and optimizing Spark workloads running on it.
- Have a good understanding and significant experience with projects using relational data models and SQL.
- Good work ethic and self-starter. You look out for issues, opportunities and address them when you can, raise them when you cannot.
- Good analytical skills and the ability to understand complexity and break it down into smaller, achievable steps.
- Highly proficient in English (written and verbal)
Though, for the right candidate, we are willing to invest in getting these skills up-tospeed alongside you!
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, including gender identity or expression, sexual orientation, age, marital status, veteran status, or disability status. Swiss Re offers modern work models and attractive workplaces that allow all employees to adapt to changing work preferences and life phases.
About Swiss Re
Swiss Re is one of the world’s leading providers of reinsurance, insurance and other forms of insurance-based risk transfer, working to make the world more resilient. We anticipate and manage a wide variety of risks, from natural catastrophes and climate change to cybercrime. We cover both Property & Casualty and Life & Health. Combining experience with creative thinking and cutting-edge expertise, we create new opportunities and solutions for our clients. This is possible thanks to the collaboration of more than 14,000 employees across the world.
Our success depends on our ability to build an inclusive culture encouraging fresh perspectives and innovative thinking. We embrace a workplace where everyone has equal opportunities to thrive and develop professionally regardless of their age, gender, race, ethnicity, gender identity and/or expression, sexual orientation, physical or mental ability, skillset, thought or other characteristics. In our inclusive and flexible environment everyone can bring their authentic selves to work and their passion for sustainability.
If you are an experienced professional returning to the workforce after a career break, we encourage you to apply for open positions that match your skills and experience.
Keywords:
Reference Code: 131892
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Agile Architecture Azure Computer Science Databricks DevOps Engineering Finance Java Pipelines PySpark Python Security Spark SQL Streaming Testing
Perks/benefits: Career development Flex hours Insurance Transparency
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