Senior Data Engineer – Capital Markets

Résumé du poste

Design, develop, and maintain scalable enterprise data warehouse and cloud-based data engineering solutions. Partner with cross-functional teams to translate business requirements into reliable data pipelines and analytical structures.

Détails du poste

We are At Synechron, we believe in the power of digital to transform businesses for the better. Our global consulting firm combines creativity and innovative technology to deliver industry-leading digital solutions. Synechron’s progressive technologies and optimization strategies span end-to-end Artificial Intelligence, Consulting, Digital, Cloud & DevOps, Data, and Software Engineering, servicing an array of noteworthy financial services and technology firms. Through research and development initiatives in our FinLabs we develop solutions for modernization, from Artificial Intelligence and Blockchain to Data Science models, Digital Underwriting, mobile-first applications and more. Over the last 20+ years, our company has been honored with multiple employer awards, recognizing our commitment to our talented teams. With top clients to boast about, Synechron has a global workforce of 17,000+, and has 58 offices in 22 countries within key global markets. Our challenge Seeking a motivated, proactive, and reliable Data Engineer to join the Data Sourcing and Analytics team. This role will support the design, development, implementation, and ongoing enhancement of enterprise data solutions across cloud data platforms. The ideal candidate will bring strong SQL programming, Snowflake, Databricks, Spark, and Python development experience, along with the ability to analyze business requirements, translate them into scalable data solutions, and collaborate effectively with technology and business stakeholders. Experience in the finance or banking domain is a strong plus. Additional Information* The base salary for this position will vary based on geography and other factors. In accordance with law, the base salary for this role if filled within Mississauga, ON is CAD $115k – CAD $130k/year & benefits (see below). The Role Responsibilities: Design, develop, and maintain scalable enterprise data warehouse, data lake, and cloud-based data engineering solutions. Develop robust ETL/ELT pipelines and transformation routines using SQL, Snowflake, Databricks, Spark, Python, and related cloud data platform services. Write, optimize, and troubleshoot complex SQL queries, stored procedures, and data transformation logic for large and complex datasets. Create and maintain data mappings, source-to-target specifications, data lineage documentation, and transformation rules to support enterprise reporting and analytics needs. Perform analysis and interpretation of business, functional, and technical requirements, and translate requirements into reliable data engineering designs. Partner with business analysts, data architects, application teams, and reporting teams to understand data needs and deliver high-quality data solutions. Support data modeling efforts, including dimensional modeling, fact and dimension design, data normalization, and fit-for-purpose analytical structures. Perform testing, validation, reconciliation, performance tuning, and production support for data pipelines and analytical datasets. Use modern engineering practices and productivity tools, including GitHub Copilot or similar AI-assisted development capabilities, to improve development efficiency and code quality. Contribute to cloud data platform migration, modernization, and operational support initiatives across the enterprise data ecosystem. Requirements: 5+ years of experience in enterprise data management, data engineering, data warehousing, or large-scale data platform development. Strong SQL programming experience, including development of complex queries, stored procedures, performance tuning, data profiling, and reverse engineering of existing data processes. Hands-on experience with Snowflake development and utilities such as SnowSQL, time travel, metadata management, data sharing, and query optimization. Hands-on experience with Databricks and Spark programming for large-scale distributed data processing, transformations, and analytical workloads. Strong Python programming experience for data processing, automation, API integration, scripting, and pipeline development. Experience with data modeling concepts, including OLTP, OLAP, dimensional modeling, facts, dimensions, and enterprise analytical data structures. Experience creating data mappings, source-to-target specifications, transformation logic, and documentation to support downstream reporting and analytics. Ability to analyze and understand business, functional, and technical requirements and convert them into scalable, maintainable data solutions. Working knowledge of cloud-based data architecture, messaging patterns, analytics platforms, and modern data engineering design principles. Experience supporting testing, validation, reconciliation, defect resolution, deployment, and production support for enterprise data solutions. Familiarity with AI-assisted development tools such as GitHub Copilot and the ability to use them responsibly to improve productivity, code quality, and documentation. Proactive self-learner with a strong commitment to quality, ownership, and accountability, with the ability to plan work effectively and deliver assignments according to agreed delivery dates. Superior communication, analytical, and problem-solving skills, with the ability to work effectively across business and technology teams. Minimally a BA degree within an engineering and/or computer science discipline Preferred, but not required: Experience in the finance or banking industry, including familiarity with securities, banking products, regulatory reporting, risk, accounting, or data footprints associated with financial instruments. Prior experience contributing to an enterprise-wide cloud data platform migration or modernization initiative. Cloud certification, Snowflake certification, Databricks certification, or related data engineering certification. Motivated, proactive, dependable, and reliable professional with a strong sense of ownership and accountability. We offer: A multinational organization with 58 offices in 22 countries and the possibility to work abroad. 15 days (3 weeks) of paid annual leave plus an additional 10 days of personal leave (floating days and sick days). A comprehensive insurance plan including medical, dental, vision, life insurance, and long-term disability. Flexible hybrid policy. RRSP with employer’s contribution up to 4%. A higher education certification policy. On-demand Udemy for Business for all Synechron employees with free access to more than 5000 curated courses. Coaching opportunities with experienced colleagues from our Financial Innovation Labs (FinLabs) and Center of Excellences (CoE) groups. Cutting edge projects at the world’s leading tier-one banks, financial institutions and insurance firms. A truly diverse, fun-loving and global work culture. S​YNECHRON’S DIVERSITY & INCLUSION STATEMENT Diversity & Inclusion are fundamental to our culture, and Synechron is proud to be an equal opportunity workplace and is an affirmative action employer. Our Diversity, Equity, and Inclusion (DEI) initiative ‘Same Difference’ is committed to fostering an inclusive culture – promoting equality, diversity and an environment that is respectful to all. We strongly believe that a diverse workforce helps build stronger, successful businesses as a global company. We encourage applicants from across diverse backgrounds, race, ethnicities, religion, age, marital status, gender, sexual orientations, or disabilities to apply. We empower our global workforce by offering flexible workplace arrangements, mentoring, internal mobility, learning and development programs, and more. All employment decisions at Synechron are based on business needs, job requirements and individual qualifications, without regard to the applicant’s gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law. Candidate Application Notice

Ce que vous ferez

Design, develop, and maintain scalable enterprise data warehouse and cloud-based data engineering solutions. Partner with cross-functional teams to translate business requirements into reliable data pipelines and analytical structures.

Exigences

Requires at least 5 years of experience in enterprise data management and strong proficiency in SQL, Snowflake, Databricks, and Python. A bachelor's degree in engineering or computer science is required.

Avantages

• Paid annual leave • Personal leave • Medical insurance • Dental insurance • Vision insurance • Life insurance • Long-term disability insurance • RRSP with employer contribution • Higher education certification policy • Udemy for Business access • Coaching opportunities

Compétences indiquées

• SQL · Souhaitée
• Python · Souhaitée

Autres compétences pertinentes

Relevées dans la description du poste. Confirmez les exigences importantes ci-dessus.

• SQL
• Snowflake
• Databricks
• Spark
• Python
• ETL/ELT pipelines
• Data warehousing
• Data modeling
• Cloud data platforms
• Data lineage
• Performance tuning
• API integration
• Dimensional modeling
• GitHub Copilot
• Data engineering
• SQL (Programming Language)
• Extract Transform Load (ETL)
• Data Structures
• Mentorship
• Communication
• Data Engineering
• Data Modeling
• Performance Tuning
• Data Warehousing
• Problem Solving
• Troubleshooting (Problem Solving)
• Business Requirements
• Solutions Support
• Innovation
• Data Science
• Pipelines
• Data Lakes
• Data Pipelines
• Snowflake (Data Warehouse)
• DevOps
• Financial Services
• Artificial Intelligence
• Consulting
• Higher Education
• Coaching
• Finance
• Design Elements And Principles
• Accountability
• Data Processing
• Data Normalization
• Equities
• Python (Programming Language)
• Software Engineering
• Data Transformation
• Data Management

Domaines d’emploi

• Data & Analytics
• Technology
• Software
• Consulting
• Finance & Accounting
• Capital Markets Manager
• Data Engineer
• Software Developers
• Database Administrators