Data Platform Engineer - 7+ Year

Job Title: Data Engineering Lead/ Data Platform Engineer Location: Toronto, Canada Experience: 7+ Years About the Role We are looking for an experienced Data Engineering Lead to design, build, and optimize scalable data platforms that support advanced analytics, AI/ML, and business intelligence initiatives. The ideal candidate will have strong expertise in Python, PySpark, Hadoop, Databricks, SQL, and cloud-based data platforms, along with proven experience leading technical teams and delivering enterprise-scale data solutions. Key Responsibilities Data Engineering Lead the ingestion, transformation, aggregation, and processing of large-scale datasets for analytics and downstream applications. Design, develop, and maintain scalable, high-performance data pipelines using Hadoop, Databricks, and enterprise data platforms. Ensure data quality, reliability, scalability, performance, and availability across data engineering workflows. Integrate structured and semi-structured data sources into unified, governed data platforms. Build and optimize ETL/ELT pipelines using modern data integration tools. Advanced Analytics Enablement Process and analyze high-volume, high-velocity datasets using big data technologies and cloud-native platforms. Develop scalable data solutions that enable advanced analytics, reporting, and AI/ML initiatives. Generate actionable insights from transactional and product data to support business growth. Establish metrics and performance benchmarks to continuously improve data solutions. Cross-Functional Collaboration Partner with Product Managers, Data Scientists, Platform teams, and Engineering stakeholders to translate business requirements into scalable data solutions. Act as the technical liaison between business and engineering teams. Communicate architectural decisions, implementation strategies, and technical trade-offs effectively. Innovation Drive innovation by developing proof of concepts (POCs), prototypes, and pilot solutions. Evaluate and integrate new technologies, data sources, and modern engineering practices. Support continuous enhancement of enterprise data platforms and products. Technical Leadership Mentor and guide data engineers while promoting engineering best practices. Establish standards for data modeling, pipeline design, governance, performance optimization, and maintainability. Drive architectural consistency and long-term platform sustainability. Lead technical discussions, code reviews, and solution design sessions. Required Skills & Experience Technical Skills 7+ years of experience in Data Engineering, Big Data, or Enterprise Data Platforms. 2+ years of experience in a technical lead or leadership role is preferred. Strong programming skills in Python, including Pandas, NumPy, and PySpark. Hands-on experience with Hadoop ecosystem and Impala. Strong expertise in SQL and working with relational as well as distributed data stores. Experience with Databricks, Snowflake, and cloud platforms (Azure and/or AWS). Experience building ETL/ELT pipelines using Apache Airflow, Apache NiFi, or Azure Data Factory. Strong knowledge of data modeling, data warehousing, and large-scale data processing. Experience implementing CI/CD pipelines and DevOps practices for data engineering. Preferred Skills Experience supporting GenAI/LLM applications through scalable data pipelines. Knowledge of processing unstructured and semi-structured data (documents, logs, text). Understanding of enterprise data governance, privacy, security, PII handling, and access controls. Familiarity with AI data workflow monitoring, data quality validation, reproducibility, and cloud cost optimization. Exposure to Machine Learning concepts, feature engineering, and model serving. Analytical & Business Skills Strong analytical and problem-solving abilities. Experience working with large, complex datasets and identifying data quality issues. Ability to translate business requirements into scalable technical solutions. Excellent communication and stakeholder management skills. Preferred Qualifications Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related field. Experience working in Agile environments. Experience delivering enterprise-scale data engineering solutions for global organizations. Our Commitment to Diversity & Inclusion Did you know that Apexon has been Certified™ by Great Place To Work®, the global authority on workplace culture, in each of the four regions in which it operates: USA (for the seventh time in 2026), India (for the tenth consecutive time in 2026), the UK (for the fourth time in 2026) and Mexico (for the second time in 2026). Apexon is committed to being an equal opportunity employer and promoting diversity in the workplace. We take affirmative action to ensure equal employment opportunity for all qualified individuals. Apexon strictly prohibits discrimination and harassment of any kind and provides equal employment opportunities to employees and applicants without regard to gender, race, color, ethnicity or national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status, or any other applicable characteristics protected by law. You can read about our Job Applicant Privacy Policy here: Job Applicant Privacy Policy (apexon.com) Our Commitment to Environment Actively contribute to Apexon's commitment to environmental responsibility by following sustainable practices and supporting ESG initiatives. Our Perks and Benefits Our benefits and rewards program has been thoughtfully designed to recognize your skills and contributions, elevate your learning/upskilling experience, and provide care and support for you and your loved ones. We also offer: Group Health Insurance covering family of 4 Term Insurance and Accident Insurance Paid Holidays & Earned Leaves Paid Parental Leave Learning & Career Development Employee Wellness Visit: www.apexon.com

The Data Engineering Lead will design, build, and optimize scalable data platforms for advanced analytics and business intelligence. They will lead the ingestion, transformation, and processing of large-scale datasets while ensuring data quality and performance.

Candidates should have 7+ years of experience in Data Engineering and strong programming skills in Python and SQL. Experience with Hadoop, Databricks, and cloud platforms is essential, along with leadership experience in technical roles.

• Group Health Insurance • Term Insurance • Accident Insurance • Paid Holidays • Earned Leaves • Paid Parental Leave • Learning & Career Development • Employee Wellness

Identified from the job description. Confirm important requirements above.

• Python
• PySpark
• Hadoop
• Databricks
• SQL
• Cloud Platforms
• ETL
• ELT
• Data Modeling
• Data Warehousing
• Big Data
• Data Engineering
• DevOps
• Machine Learning
• Data Governance
• Data Quality

• Technology
• Data & Analytics
• Software

Minimum education

Bachelor’s degree

Minimum experience

7+ years

Apply by

Aug 12, 2026

Posting language

English

Working hours

40 hours per week

Seniority

Mid-Senior level

Application method

Direct apply is available