Data Engineer

We are seeking a skilled and proactive Data Engineer to design, build, and maintain robust, scalable, and optimized data pipelines and architectures. In this role, you will collaborate closely with Data Scientists, Business Intelligence Analysts, and Software Engineers to transform raw enterprise data into clean, accessible, and high-performance data models. The ideal candidate has hands-on experience with modern cloud data platforms, distributed computing, streaming and batch ETL/ELT pipelines, data modeling, and robust data governance practices.

Responsibilities

• Pipeline Development & Architecture Design & Build ETL/ELT Pipelines: Develop scalable batch and real-time streaming data ingestion and transformation pipelines from diverse sources (APIs, transactional DBs, Kafka, logs, flat files).
• Architect and optimize dimensional data models (Star/Snowflake schemas, One Big Table), data lakes, data lakehouses, and relational/NoSQL data stores.
• Implement and maintain pipeline scheduling, dependency management, and monitoring using modern orchestrators (e.g., Apache Airflow, Prefect, Dagster).
• Performance, Reliability & Scalability Query & Storage Optimization: Fine-tune SQL queries, indexing, partitioning, caching, and distributed compute workloads (e.g., Spark, Trino, DuckDB).
• Implement automated data validation, anomaly detection, and schema evolution testing (e.g., Great Expectations, Soda, dbt tests).
• Build observability frameworks for pipeline uptime, latency, SLA adherence, and data freshness.
• & Governance Data Governance & Security: Enforce enterprise data security, role-based access control (RBAC), data lineage, and compliance standards (GDPR, CCPA, SOC2, HIPAA).
• Partner with downstream data consumers (BI developers, ML engineers, business stakeholders) to understand data requirements and deliver self-service datasets.
• Champion Infrastructure as Code (Terraform), containerization (Docker, Kubernetes), and CI/CD best practices for data products.

Requirements

• Qualifications & Skills Technical Competencies Programming Languages: Proficiency in Python and/or Scala/Java , with strong knowledge of software engineering best practices (OOP, clean code, unit testing, git).
• Advanced SQL proficiency; deep expertise in modern cloud data warehouses (e.g., Snowflake, Google BigQuery, AWS Redshift, Databricks Lakehouse ).
• Hands-on experience with Apache Spark / PySpark , Apache Flink, or Hadoop ecosystems.

Preferred

• Experience with modern data stack tools such as dbt (data build tool) and Apache Airflow .
• Solid experience with at least one major cloud provider ( AWS, GCP, or Azure ) and core data services (e.g., S3/GCS/ADLS, Glue, EMR, BigQuery, Lambda/Cloud Functions).

5+ years of experience leading complex data platform implementations and architecture decisions. ------------------------------------------------------ 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. ------------------------------------------------------ Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law. If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity review Accessibility at Citi . View Citi’s EEO Policy Statement and the Know Your Rights poster.