Big Data & SQL Developer

PowerToFly; Mississauga; On-site; CAD 100,000 - 130,000; Full time

Job summary

A leading technology firm in Mississauga is looking for a senior Big Data and SQL Developer to establish and implement cutting-edge data solutions. The role focuses on designing and building scalable systems, mentoring engineers, and engaging with clients to address their business needs. Candidates should have 6+ years of experience in software engineering, deep technical proficiency in Big Data frameworks like Apache Spark, and strong client management skills. This position offers an opportunity to lead significant technical initiatives in a dynamic environment.

Qualifications

• 6+ years of progressive experience in software engineering focused on Big Data systems.
• Proven track record in significant data initiatives with a lead role.
• Experience in financial services with large data volumes and real-time processing.

Responsibilities

• Lead the design and implementation of scalable Big Data solutions.
• Mentor junior engineers and provide technical guidance.
• Act as a liaison for business requirements and technical solutions.

Skills

Big Data Solutions

SQL proficiency

Scala

Python

Java

Data Warehousing

Client Management

Analytical Skills

Education

Bachelor’s degree

Master’s degree preferred

Tools

Apache Spark

Hadoop

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

• 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.

Qualifications

• 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.

Education

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

This job opening is for an existing job vacancy.

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