data
1 hour ago*
Lead Data Engineer
at Visa
📍 Us Bellevue, United States·🏢 On-site
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Responsibilities
- The Lead Data Engineer drives technical best practices, ensures platform scalability, and influences data engineering strategy for key products and business domains.
- Design scalable data models, lakehouse structures, and distributed data processing solutions that support analytics, machine learning, and real-time data needs.
- Develop and improve engineering best practices for data governance, quality, observability, testing, and cloud resource optimization.
- Drive adoption of cloud-native data technologies, automation frameworks, and reusable components that improve development velocity and system reliability.
- Lead complex data modernization efforts, including cloud migration, data lake/lakehouse consolidation, and performance optimization of critical pipelines.
- Evaluate new tools and technologies, influencing platform evolution within the scope of assigned domains or product areas.
- Collaborate with product, analytics, and platform teams to ensure alignment on data strategy and architectural roadmaps.
- Mentor engineers at all levels, providing technical coaching and fostering a culture of continuous improvement.
Requirements
- Job Description The Lead Data Engineer is a senior technical leader responsible for guiding the design, development, and optimization of Visa’s large‑scale data platforms and cloud-based analytics environments.
- Qualifications Basic
- Advanced expertise in building and optimizing large-scale distributed data systems using Hadoop, Spark, and modern lakehouse architectures.
- Strong programming proficiency in PySpark, Scala, and Python with
- experience implementing scalable, production-grade data applications. Deep
- experience designing and tuning RDBMS, NoSQL, and distributed SQL systems.
- Mastery of SQL and distributed query engines such as Presto, Trino, Hive, and SparkSQL.
- Strong knowledge of data modeling, ETL/ELT design, and data warehousing methodologies. Proven
- experience architecting and operating data solutions on AWS, GCP, and Azure, including cloud data lakes, orchestration tools, and cost-effective storage/compute designs.
- Advanced proficiency in Databricks, including: