Senior Data Engineering Lead - Vice President

Overview

The Applications Development Technology Lead Analyst is a senior-level position responsible for leading application systems analysis and programming activities and establishing and implementing new or revised application systems and programs. As Data Engineering Lead for Global Wealth Data, the role defines data engineering direction, leads a globally distributed team, and delivers scalable data solutions supporting wealth management stakeholders.

What you'll do

• Define and execute the data engineering roadmap for Global Wealth Data, aligning with business objectives and technology strategy.
• Understand the data needs of portfolio managers, investment advisors, and other stakeholders in the wealth management ecosystem.
• Lead, mentor, and develop a high-performing, globally distributed team of data engineers.
• Foster a culture of collaboration, innovation, and continuous improvement.
• Oversee the design and implementation of robust and scalable data pipelines, data warehouses, and data lakes.
• Ensure data quality, integrity, and availability for global wealth data.
• Design solutions for handling large volumes of structured and unstructured data from various sources.
• Evaluate and select appropriate technologies and tools for data engineering.
• Stay abreast of industry best practices and emerging trends specific to wealth management data.
• Monitor and optimize data pipelines and infrastructure for performance, scalability, and cost-effectiveness.
• Partner with business stakeholders, data scientists, portfolio managers, and other technology teams to understand data needs and deliver effective solutions supporting investment strategies and client reporting.
• Implement and enforce data governance policies and procedures for data quality, security, and compliance with relevant regulations, particularly around sensitive financial data.
• Establish and implement new or revised application systems and programs in coordination with the Technology team.
• Provide advice and counsel related to the technology or operations of the business.

What you'll need

• Bachelor’s/University degree or equivalent experience in computer science, engineering, or similar domain.
• 10-15 years of hands-on experience in Hadoop, Scala, Java, Spark, Hive, Kafka, Impala, Unix Scripting and other Big data frameworks.
• 4+ years of experience with relational SQL and NoSQL databases: Oracle, MongoDB, HBase.
• Strong proficiency in Python and Spark Java with knowledge of core spark concepts, including RDDs, Dataframes, Spark Streaming, and Scala and SQL.
• Data Integration, Migration & Large Scale ETL experience, including ETL design & build, handling, reconciliation and normalization.
• Data Modeling experience, including OLAP, OLTP, Logical/Physical Modeling, Normalization, and knowledge on performance tuning.
• Experience working with large and multiple datasets and data warehouses.
• Experience building and optimizing ‘big data’ data pipelines, architectures, and datasets.
• Strong analytic skills and experience working with unstructured datasets.
• Ability to effectively use complex analytical, interpretive, and problem-solving techniques.
• Experience with Confluent Kafka, Redhat JBPM, CI/CD build pipelines and toolchain – Git, BitBucket, Jira.
• Experience with external cloud platform such as OpenShift, AWS & GCP.
• Experience with container technologies, including Docker and Pivotal Cloud Foundry, and supporting frameworks, including Kubernetes, OpenShift, and Mesos.
• Experience integrating search solution with middleware & distributed messaging - Kafka.
• Highly effective interpersonal and communication skills with tech/non-tech stakeholders.
• Experience in software development life cycle and good problem-solving skills.
• Excellent problem-solving skills and strong mathematical and analytical mindset.
• Ability to work in a fast-paced financial environment.

Details

• Location: Pune, Maharashtra, India.
• Employment type: Full time.