Job Description: Big Data Engineering Lead

The Vice President, Big Data Engineering Lead is a senior leadership role responsible for directing a team of specialized engineers in the design, development, and strategic management of the organization's large-scale data infrastructure and platforms. As a subject matter expert, this individual will blend deep technical mastery of big data technologies with strategic vision to solve complex data challenges and drive innovation. This role requires the integration of in-depth knowledge of the data engineering domain with a comprehensive understanding of industry’s best practices, business objectives, and regulatory landscapes. The successful candidate will have a substantial impact on the business by setting the technical direction for data engineering, ensuring the delivery of robust and scalable data solutions, and fostering a world-class engineering team.

Responsibilities:

• Leads and mentors a team of big data engineers, guiding the planning, architecture, and implementation of highly scalable and reliable data processing systems and data lakes.
• Sets the technical vision and strategy for the big data platform, ensuring alignment with the firm's overall technology roadmap and business goals.
• Drives the adoption of best practices in data engineering, including advanced ETL/ELT strategies, data modeling, CI/CD for data pipelines, automated data quality checks, and secure data handling.
• Architects and oversees the development of robust, production-grade data pipelines capable of ingesting and processing high-velocity data from a multitude of sources.
• Partners with senior stakeholders, including data science leaders, business executives, and product managers, to define data requirements and deliver impactful data solutions.
• Make critical evaluative judgments on complex data architecture challenges, resolving high-impact problems by designing and selecting innovative solutions based on extensive experience.
• Governs the health, performance, and cost-efficiency of distributed computing environments and cloud data services, ensuring optimal reliability and scalability.
• Contributes to the firm's data governance framework, ensuring that data is managed as a critical asset with appropriate security, privacy, and compliance controls.
• Evaluates emerging technologies in the big data ecosystem and champions their adoption where they can provide a competitive advantage.
• Manages resource planning, project execution, and stakeholder communication for all major data engineering initiatives.
• Appropriately assess risk when business decisions are made, demonstrating particular consideration for the firm's reputation and safeguarding Citigroup, its clients and assets, by driving compliance with applicable laws, rules and regulations, adhering to Policy, applying sound ethical judgment regarding personal behavior, conduct and business practices, and escalating, managing and reporting control issues with transparency.

Qualifications:

• 13+ years of experience in data engineering or software engineering, with a clear progression into roles focused on large-scale data challenges.
• At least 3-5 years of experience in a formal leadership capacity, with a proven ability to build, mentor, and lead high-performing engineering teams.
• Extensive experience with distributed data processing frameworks such as Apache Spark, Hadoop, Hive, HBase, Sqoop, Flume or Flink.
• Extensive hands-on experience designing and building data solutions on public cloud platforms (e.g., AWS, Azure, Google Cloud), utilizing services like S3, EMR, Redshift, BigQuery, and Synapse.
• Deep expertise in data warehousing architecture, data modeling, and managing enterprise-scale data lakes.
• Demonstrated ability to think strategically, with strong analytical and problem-solving skills to navigate complex technical and business issues.
• Excellent communication, interpersonal, and leadership skills, with the ability to influence and align senior and executive stakeholders.
• Proven ability to work to deadlines in a fast-paced, agile environment

Education:

• Bachelor’s/University degree in Computer Science, Engineering, or a related quantitative discipline, or equivalent experience.
• Master’s degree or higher is strongly preferred.
• Proficiency in programming languages such as Python, Scala, or Java for data-intensive applications.
• Strong experience with stream-processing systems (e.g., Kafka, Kinesis) and **NoSQL **databases.

Job Family Group:

Technology

Job Family:

Applications Development

Time Type:

Full time

Most Relevant Skills

Please see the requirements listed above.

Other Relevant Skills

For complementary skills, please see above and/or contact the recruiter.

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