Big Data & SQL Developer - Vice President

Citi; Mississauga; On-site; CAD 168,000 - 239,000; Full time

Job summary

A leading global financial services firm in Mississauga is seeking a Big Data and SQL Developer. This role requires strong technical expertise in designing scalable solutions and mentoring other engineers. The ideal candidate has a robust background in Big Data systems and financial services, along with excellent communication skills. Key responsibilities include leading technical projects, optimizing data solutions, and collaborating with stakeholders to drive strategic initiatives.

Qualifications

• 6+ years of experience in software engineering with Big Data systems.
• Proficient in stakeholder management and building client relationships.
• Experience in financial services focused on Liquidity Management.

Responsibilities

• Lead design and implementation of Big Data solutions.
• Mentor junior engineers and guide technical teams.
• Engage stakeholders to gather and translate business requirements.

Skills

Big Data solutions

Scala

Python

Java

SQL

Apache Spark

Data Governance

DevOps

Education

Bachelor’s degree

Master’s degree

Tools

Apache Spark

Hadoop

CI/CD

Docker

Kubernetes

Job description

Overview

The Big Data and SQL Developer is a senior level position responsible for establishing and implementing new or revised application systems and programs in coordination with the Technology team. The overall objective of this role is to lead applications systems analysis and programming activities.

Responsibilities

This role balances hands-on technical work with strategic influence, mentorship, and vital stakeholder engagement:

• Technical Design & Implementation (60-70%):
  • Architecture & Design: Lead the design and implementation of highly scalable, robust, and performant Big Data solutions, including data warehouses, streaming platforms, and analytical systems.
  • Hands-on Development: Write high-quality, production-ready code for complex data pipelines, processing frameworks, and analytical tools using languages like Scala, Python, or Java.
  • Performance Optimization: Drive performance tuning, troubleshooting, and optimization of Big Data applications and infrastructure.
  • Technical Problem Solving: Act as a go-to expert for resolving complex technical challenges across the Big Data ecosystem.
  • Innovation: Research, evaluate, and integrate new Big Data technologies and tools to enhance existing platforms and capabilities.
  • Best Practices: Champion and enforce engineering best practices, including code quality, testing, CI/CD, and documentation.
• Technical Leadership & Mentorship (15-20%):
  • Technical Guidance: Provide technical leadership and guidance to multiple engineering teams, ensuring alignment with architectural principles and strategic goals.
  • Mentorship: Mentor senior and junior engineers, fostering their technical growth, problem-solving skills, and adherence to best practices.
  • Code Review & Quality Assurance: Lead comprehensive code reviews, ensuring high standards of code quality, efficiency, and maintainability.
  • Strategic Input: Contribute significantly to the Big Data strategy and roadmap, influencing technical decisions and long-term planning.
  • Knowledge Sharing: Drive initiatives for knowledge sharing, technical documentation, and community building within the Big Data engineering group.
  • Recruitment Support: Participate in interviewing and evaluating senior technical candidates.
• Stakeholder Management & Client Engagement:
  • Client & Business Partner Liaison: Act as a key technical liaison between the Big Data engineering team and internal business units, product managers, and clients.
  • Requirements Gathering: Proactively engage with stakeholders to understand business requirements, pain points, and opportunities, translating them into clear, actionable technical specifications and data solutions.
  • Technical Consultation: Provide expert technical consultation and guidance to clients and business partners on Big Data capabilities, limitations, and potential solutions.
  • Query Resolution: Assist clients and internal stakeholders with complex data queries, troubleshooting data discrepancies, and providing insights derived from Big Data platforms.
  • Communication: Effectively communicate complex technical concepts, project progress, risks, and solutions to non-technical audiences, ensuring transparency and alignment.
  • Cross-Functional Collaboration: Collaborate seamlessly with other teams (e.g., architecture, data sourcing) to ensure end-to-end delivery and support of data-driven initiatives.
• Leadership, Communication & Interpersonal Skills:
  • Exceptional problem-solving and analytical skills, with the ability to tackle highly complex technical and business challenges.
  • Strong architectural thinking and the ability to design solutions that are scalable, maintainable, and resilient.
  • Excellent verbal and written communication skills, with a proven ability to tailor technical explanations to diverse audiences, from engineers to senior business stakeholders and external clients.
  • Demonstrated ability to build consensus, manage expectations, and influence outcomes with various stakeholders.
  • Experience in mentoring and coaching other engineers.
  • Proactive, self-motivated, and able to work effectively in a fast-paced, agile environment, often juggling multiple priorities.

Education

• Bachelor’s degree/University degree or equivalent experience
• Master’s degree preferred

Experience

• 6+ years of progressive experience in software engineering, specifically focused on designing, building, and optimizing large-scale Big Data systems.
• Proven track record as a lead or principal engineer on significant data initiatives, demonstrating ability to drive technical projects from conception to deployment.
• Significant experience in client-facing or business partner-facing roles, with a proven ability to manage expectations, resolve issues, and build strong relationships.
• Experience in the financial services domain – Liquidity Management, Liquidity Stress Modelling, should be well verse with Markets terminologies. Also, experience with large data volumes, real-time processing, and stringent data quality/security requirements.

Deep Technical Proficiency

• Core Big Data Frameworks: Expert-level proficiency with Apache Spark (Spark SQL, Spark Streaming, PySpark/Scala Spark), Hadoop ecosystem (HDFS, YARN).
• Programming Languages: Expert in Scala, Python, or Java, with experience in developing robust, high-performance data processing applications.
• Data Warehousing/Lakes: Deep understanding and practical experience with data warehouse models, and relevant technologies (e.g., Delta Lake, Iceberg, Parquet).
• Databases: Strong proficiency in SQL; experience with NoSQL databases (e.g., Cassandra, MongoDB) is a plus.
• DevOps & MLOps: Experience with CI/CD pipelines (e.g., Jenkins, GitLab CI), infrastructure as code (e.g., Terraform), containerization (Docker, Kubernetes/OpenShift), and monitoring tools. Familiarity with MLOps principles for data science workflows. Data Governance & Security: Solid understanding of data governance, data quality, data lineage, and data security principles in a Big Data environment.

Job Information

Time Type: Full time

Primary Location Full Time Salary Range: $120,800.00 - $170,800.00

Other

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.

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