The Engineering Lead Analyst is a senior level position responsible for leading a variety of engineering activities including the design, acquisition and deployment of hardware, software and network infrastructure in coordination with the Technology team. The overall objective of this role is to lead efforts to ensure quality standards are being met within existing and planned framework.
Responsibilities:
- Strategic Leadership: Define and execute the data engineering roadmap for Global Wealth Data, aligning with overall business objectives and technology strategy. This includes understanding the data needs of portfolio managers, investment advisors, and other stakeholders in the wealth management ecosystem.
- Team Management: Lead, mentor, and develop a high-performing, globally distributed team of data engineers, fostering a culture of collaboration, innovation, and continuous improvement.
- Architecture and Design: Oversee the design and implementation of robust and scalable data pipelines, data warehouses, and data lakes, ensuring data quality, integrity, and availability for global wealth data. This includes designing solutions for handling large volumes of structured and unstructured data from various sources.
- Technology Selection and Implementation: Evaluate and select appropriate technologies and tools for data engineering, staying abreast of industry best practices and emerging trends specific to wealth management data.
- Performance Optimization: Continuously monitor and optimize data pipelines and infrastructure for performance, scalability, and cost-effectiveness, ensuring optimal access to global wealth data.
- Collaboration: Partner with business stakeholders, data scientists, portfolio managers, and other technology teams to understand data needs and deliver effective solutions that support investment strategies and client reporting.
- Data Governance: Implement and enforce data governance policies and procedures to ensure data quality, security, and compliance with relevant regulations, particularly around sensitive financial data.
Qualifications:
- 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 (RDDs, Dataframes, Spark Streaming, etc) and Scala and SQL
- Data Integration, Migration & Large Scale ETL experience (Common ETL platforms such as PySpark/DataStage/AbInitio etc.) - ETL design & build, handling, reconciliation and normalization
- Data Modeling experience (OLAP, OLTP, Logical/Physical Modeling, Normalization, knowledge on performance tuning)
- Experienced in 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 (Docker, Pivotal Cloud Foundry) and supporting frameworks (Kubernetes, OpenShift, Mesos)
- Experienced in integrating search solution with middleware & distributed messaging - Kafka
- Highly effective interpersonal and communication skills with tech/non-tech stakeholders.
- Experienced 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
Education:
- Bachelor’s degree/University degree or equivalent experience
- Master’s degree preferred
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Job Family Group:
Technology------------------------------------------------------
Job Family:
Systems & Engineering------------------------------------------------------
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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Skills Required
- 10-15 years hands-on experience with Hadoop, Scala, Java, Spark, Hive, Kafka, Impala, Unix scripting and other big data frameworks
- 4+ years experience with relational and NoSQL databases: Oracle, MongoDB, HBase
- Strong proficiency in Python and Spark (core concepts: RDDs, DataFrames, Spark Streaming)
- Experience with large-scale ETL, data integration and migration (PySpark/DataStage/AbInitio)
- Data modeling experience (OLAP, OLTP, logical/physical modeling, normalization, performance tuning)
- Experience building and optimizing big data pipelines, architectures, and datasets
- Experience working with unstructured datasets and strong analytical/problem-solving skills
- Experience with Confluent Kafka and integrating search solutions with middleware/distributed messaging
- Experience with CI/CD toolchain and pipelines (Git, BitBucket, Jira)
- Experience with cloud and platform technologies: OpenShift, AWS, GCP
- Experience with container technologies and orchestration: Docker, Pivotal Cloud Foundry, Kubernetes, Mesos
- Experience with Redhat JBPM
- Experienced in software development life cycle and ability to work in fast-paced financial environment
- Highly effective interpersonal and communication skills with technical and non-technical stakeholders
- Bachelor's degree or equivalent experience
- Master's degree
Citi Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Citi and has not been reviewed or approved by Citi.
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Healthcare Strength — Health coverage is presented as comprehensive, including free in-network preventive care, mental-health resources, and the Be Well Program. Materials also state new hires have access to health and insurance benefits from the outset.
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Retirement Support — The retirement plan offers a $1-for-$1 match up to 6% of eligible pay. New employees are eligible for the plan, with automatic enrollment after 90 days if they do not enroll themselves.
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Inclusive Benefits Coverage — Benefits highlight fertility treatment coverage, adoption/surrogacy reimbursement up to $30,000, and disability coverage. Coverage extends to spouses and domestic partners regardless of gender identity or sexuality, with gender-affirming care-related support noted.
Citi Insights
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