Sr. Data Engineer (Hadoop, Bigdata)

• 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. Hybrid employees can alternate time between both remote and office. Employees in hybrid roles are expected to work from the office 2-3 set days a week (determined by leadership/site), with a general guidepost of being in the office 50% or more of the time based on business needs.

• 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.

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.

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.