Staff Data Engineer

Visa is a world leader in payments and technology, with over 259 billion payments transactions flowing safely between consumers, merchants, financial institutions, and government entities in more than 200 countries and territories each year. Our mission is to connect the world through the most innovative, convenient, reliable, and secure payments network, enabling individuals, businesses, and economies to thrive while driven by a common purpose – to uplift everyone, everywhere by being the best way to pay and be paid.

Make an impact with a purpose-driven industry leader. Join us today and experience Life at Visa.

The Senior Data Engineer role involves leading and mentoring a team of data engineers, coordinating with other teams to manage and prioritize projects, and driving the strategy, roadmap, and execution of key data engineering initiatives. The role requires understanding and translating business needs into data models, creating robust data pipelines, and developing and maintaining data lakes. It also involves implementing and maintaining CI/CD pipelines for data solutions. The candidate should be able to define and manage data load procedures, implement data strategies, and ensure robust operational data management systems. Collaborating with stakeholders across the organization to understand their data needs and deliver solutions is also a key part of this role. The ideal candidate will be proficient in big data tools like Hadoop, Hive, and Spark, programming languages such as Scala, Python, SQL, and have strong analytical skills related to working with structured and unstructured datasets.

This position is based in Visa's offices in Bangalore, India, and presents an excellent opportunity for those looking to make a significant impact in the field of Data Engineering.

Essential Functions:

• Experience in Requirement Gathering, Estimating, Managing large scale Data Engineering Projects.
• Requirement Analysis: Understand and translate business needs into data models supporting long-term solutions.
• Data Modeling: Work with the Business team to implement data strategies, build data flows and develop conceptual data models.
• Data Pipeline Design: Create robust and scalable data pipelines and data products in a variety of domains.
• Data Integration: Develop and maintain data lakes by acquiring data from primary and secondary sources and build scripts that will make our data evaluation process more flexible or scalable across data sets.
• Testing: Define and manage the data load procedures to reject or discard datasets or data points that do not meet the defined business rules and quality thresholds.
• Deployment: Implement data strategies and develop physical data models, along with the development teams, data analyst teams and information system team to ensure robust operational data management systems.
• Understanding of and ability to Implement Data Engineering principles and best practices.
• Team Leadership: Lead and mentor a team of data engineers. Coordinate with other teams to manage and prioritize projects. Drive strategy, roadmap, and execution of key data engineering initiatives.
• Stakeholder Management: Collaborate with stakeholders across the organization to understand their data needs and deliver solutions.
• Continuous Integration and Continuous Deployment (CI/CD): Implement and maintain CI/CD pipelines for data solutions, ensuring rapid, reliable, and streamlined updates to the data environment.

This is a hybrid position. Expectation of days in office will be confirmed by your hiring manager.

Technical Skills:

• Extensive experience in big data tools: Hadoop, Hive, and Spark.
• Proficiency in Scala, Python, SQL, and PySpark.
• Experience with Unix/Linux systems with scripting experience in Bash.
• Experience with data pipeline and workflow management tools like Airflow, etc.
• Experience with relational SQL and NoSQL databases, including Postgres and Cassandra.
• Experience with cloud services AWS or Azure.
• Experience with stream-processing systems: Kafka, Spark-Streaming, etc.
• Strong analytic skills related to working with structured & unstructured datasets.
• Proficiency in managing and communicating data warehouse plans to internal clients.
• Experience with building processes supporting data transformation, data structures, metadata, dependency, and workload management.
• A successful history of manipulating, processing, and extracting value from large, disconnected datasets.
Other Skills:
• Strong problem-solving skills.
• Excellent communication skills.
• Ability to work in a team.
• Detail-oriented and excellent organizational skills.

Qualifications:
• 8+ years of work experience with a bachelor’s degree or at least 5+ years of work experience with an Advanced degree (e.g. Master’s, MBA, JD, MD) or 3+ years of work experience with a PhD degree
• Exposure to Financial Services/ Payments Industry
• Proven leadership skills with experience leading a team of data engineers.
Leadership Competencies
• Exhibits intellectual curiosity and a desire for continuous learning.
• Demonstrates integrity, maturity, and a constructive approach to business challenges.
• Role model for the organization and implementing core Visa Values
• Respect for the Individuals at all levels in the workplace
• Strive for Excellence and extraordinary results.
• Use sound insights and judgments to make informed decisions in line with business strategy and needs.
• Leadership skills include an ability to allocate tasks and resources across multiple lines of businesses and geographies. Leadership extends to ability to influence senior management within and outside Analytics groups.
• Ability to successfully persuade/influence internal stakeholders for building best-in-class solutions.

Visa is an EEO Employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status. Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with EEOC guidelines and applicable local law.