Technology Lead - Informatica Developer

We are seeking an experienced Data Engineer to design, develop, and support enterprise data engineering and analytics solutions across modern cloud platforms. The ideal candidate will have hands‑on experience with the complete project life cycle — from requirements gathering and design through development, testing, deployment, and post‑production support — along with strong technical expertise in Python, Snowflake, Azure Data Factory (ADF) or Microsoft Fabric, and advanced SQL. This role requires strong UNIX/Linux shell scripting skills to build, optimize, and troubleshoot complex data pipelines supporting business‑critical data and analytics initiatives.
Required Qualifications
Candidates authorized to work for any employer in Canada without employer‑based visa sponsorship are welcome to apply. Infosys is unable to provide immigration sponsorship for this role at this time.
Candidate must be located within commuting distance of Mississauga, ON / Calgary, AB / Burnaby, BC or be willing to relocate to the areas.
Bachelor's degree or foreign equivalent required from an accredited institution. Will also consider three years of progressive experience in the specialty in lieu of every year of education.
At least 4 years of Information Technology experience, including hands‑on data engineering or ETL/ELT development.
Preferred Qualifications
Strong hands‑on experience with Python for data pipeline development, automation, and scripting (e.G., pandas, PySpark, or similar libraries).
Experience building and managing data pipelines and warehousing solutions in Snowflake (e.G., Streams, Tasks, Pipes, warehouses, role‑based access, performance/cost optimization).
Hands‑on experience with Azure Data Factory (ADF) and/or Microsoft Fabric for cloud‑based data integration, orchestration, and transformation.
Strong proficiency in SQL (complex queries, joins, stored procedures, performance tuning) on any major RDBMS or cloud data warehouse (Snowflake, Azure SQL, Synapse, Oracle, SQL Server, etc.).
UNIX/Linux shell scripting for automation, job scheduling, and file/data handling.
Experience with ETL/ELT performance tuning and troubleshooting.
Knowledge of job scheduling/orchestration tools (e.G., Airflow, Control-M, Autosys, ADF triggers/pipelines) is a plus.
Familiarity with data warehousing concepts, dimensional modeling, and data governance practices.
End‑to‑end exposure to project phases: initiation, requirement analysis, design, build, testing, UAT, deployment, and warranty/support.
Experience working in Agile/Scrum or Waterfall project environments.
Ability to prepare and review technical design documents, test plans, and deployment plans.
Experience coordinating with cross‑functional teams (business, QA, infrastructure, DBA) to ensure on‑time, quality delivery.
Familiarity with change management, version control (e.G., Git), and release management practices.
Key Responsibilities
Participate in the complete project life cycle (PLC) — requirement gathering, analysis, design, development, unit testing, UAT support, deployment, and post‑go‑live support.
Design, develop, and maintain data pipelines and workflows using Python, Snowflake, and Azure Data Factory (ADF) or Microsoft Fabric.
Build and manage cloud‑native data integration and transformation pipelines, including ingestion, staging, and curated/analytics‑ready layers in Snowflake.
Analyze business and functional requirements and translate them into technical design documents (source‑to‑target mappings, pipeline design specs).
Develop and optimize complex SQL queries, stored procedures, and views for data extraction, transformation, and validation.
Write and maintain UNIX/Linux shell scripts for job scheduling, file handling, automation, and workflow orchestration.
Perform data profiling, data quality checks, and error handling within data pipelines.
Conduct performance tuning of pipelines, warehouses, and SQL queries to improve throughput and reduce processing time/cost.
Collaborate with business analysts, DBAs, QA teams, and project managers throughout all SDLC/PLC phases.
Prepare and maintain technical documentation, including design documents, unit test cases, and deployment/run‑books.
Support migration/modernization activities onto Snowflake, ADF, and/or Microsoft Fabric platforms.
Troubleshoot production issues, perform root cause analysis, and implement permanent fixes.
Adhere to coding standards, version control practices, and change management/release processes.
Provide effort estimates, status updates, and risk assessments to project managers and stakeholders.
Nice To Have
Experience with additional cloud data platforms (e.G., Azure Synapse, Databricks, or AWS Redshift).
Exposure to API‑based integrations and event‑driven/streaming data pipelines.
Knowledge of Informatica or other ETL tools as a complement to modern cloud‑native pipelines.
Experience with CI/CD pipelines for data engineering deployments.
Estimated annual compensation range for the candidate based in the below location will be:
Ontario$ 92740 to $ 123375
British Columbia$ 90450 to $ 136500
The job entails sitting as well as working at a computer for extended periods of time. Should be able to communicate by telephone, email or face to face. Travel may be required as per the job requirements
About UsInfosys is a global leader in next‑generation digital services and consulting. We enable clients in more than 50 countries to navigate their digital transformation. With over four decades of experience in managing the systems and workings of global enterprises, we expertly steer our clients through their digital journey. We do it by enabling the enterprise with an AI‑powered core that helps prioritize the execution of change. We also empower the business with agile digital at scale to deliver unprecedented levels of performance and customer delight. Our always‑on learning agenda drives their continuous improvement through building and transferring digital skills, expertise, and ideas from our innovation ecosystem.
EEOInfosys provides equal employment opportunities to applicants and employees without regard to race;
color;
sex;
gender identity;
sexual orientation;
religious practices and observances;
national origin;
pregnancy, childbirth, or related medical conditions;
status as a protected veteran or spouse/family member of a protected veteran;
or disability.
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