2 months ago
Mississauga, CanadaSenior
Base Salary
$121k - $171k/yr
Responsibilities
- Design, develop, and maintain scalable Python-based data pipelines for data ingestion, transformation, and distribution.
- Build reusable Python libraries, frameworks, and automation utilities for data engineering workflows.
- Develop and optimize complex SQL queries, stored procedures, and database objects across relational database platforms.
- Design and implement ETL/ELT solutions with staging frameworks, incremental processing, reconciliation, and error handling.
- Develop and maintain logical, physical, relational, and dimensional data models for operational and analytical use cases.
- Design data structures and access patterns for NoSQL workloads, particularly MongoDB.
- Build and maintain PySpark pipelines for large-scale distributed data processing.
- Implement data quality, validation, completeness, governance, security, and compliance controls.
- Collaborate with data scientists, analysts, software engineers, and business stakeholders to deliver data solutions.
- Contribute to automated testing, deployment, version control, code reviews, troubleshooting, debugging, and production support for data systems.
Requirements
- Strong proficiency in Python for data transformation, orchestration, workflow automation, and utility development.
- Expert-level SQL skills with relational databases such as PostgreSQL, Oracle, SQL Server, or MySQL.
- Solid experience with relational and dimensional data modeling, including Star and Snowflake schemas.
- Hands-on experience designing and building Python-based ETL/ELT pipelines.
- Working experience with NoSQL databases, particularly MongoDB.
- Six or more years of total software or data engineering experience.
- Proven experience building and maintaining production-grade data pipelines and platforms at enterprise scale.
- Hands-on experience with Python-based data engineering, SQL development, ETL design, and data modeling.
- Experience with relational and NoSQL databases in real-world projects.
- Experience in regulated or highly process-oriented environments, preferably financial services.
- Experience with PySpark and distributed data processing is advantageous.
- Familiarity with Databricks, Starburst, Apache Airflow or equivalent schedulers, and data formats including Parquet, Avro, and JSON is advantageous or required as specified.
- Experience with AI development tools such as Claude Code, Devin AI, Cursor, or Copilot.
- Proficiency with Git and CI/CD practices for data engineering workflows.
- Knowledge of storage platforms such as HDFS or cloud object stores.
- Basic working knowledge of Java is advantageous.
- Bachelor's or master's degree in Computer Science, Software Engineering, or an equivalent technical field.
Benefits
- Full-time position.
- Primary location full-time salary range is $120,800.00–$170,800.00.
Tech Stack
Categories
Data Engineering
About Citi
Citi is a public financial-services company offering consumer and institutional banking, credit cards, wealth management, treasury and trade solutions, and capital-markets services. It serves individuals, corporations, financial institutions, and governments in more than 160 countries and jurisdictions, earning interest and fee income from lending, payments, trading, and advisory. Founded in 1812 and headquartered in New York, it trades on the NYSE under the ticker C.