Adastra is seeking a Senior Data Engineer to design, build, and optimize scalable data pipelines and cloud-based data platforms that support advanced analytics, reporting, and AI initiatives. This role is responsible for developing high-performance ETL/ELT solutions using PySpark and modern data engineering technologies, enabling efficient processing of large-scale structured and semi-structured data across enterprise environments. The ideal candidate is a hands-on data engineering professional with strong expertise in distributed data processing, cloud data platforms, and data pipeline orchestration.

This individual will collaborate closely with data architects, data scientists, analysts, and business stakeholders to deliver reliable, scalable, and high-quality data solutions that drive business value and support data-driven decision-making.

Employment Type: Full-Time or Contractor Design, develop, and maintain scalable ETL/ELT pipelines using PySpark for batch and near-real-time data processing Develop and optimize Spark jobs using DataFrames, RDDs, and Spark SQL for large-scale data transformations and aggregations Build reusable data ingestion frameworks to support integration from databases, APIs, flat files, and streaming sources Optimize Spark application performance through partitioning, caching, broadcast joins, and cluster resource tuning Collaborate with data scientists, analysts, and business stakeholders to deliver clean, curated datasets for reporting and advanced analytics Implement automated data quality checks, validation rules, and monitoring processes to ensure data reliability Integrate data pipelines with cloud data lakes and data warehouse platforms such as Snowflake, Redshift, Delta Lake, S3, and HDFS Troubleshoot and resolve pipeline failures, production issues, and distributed processing bottlenecks Maintain technical documentation, version control, and deployment processes for data engineering solutions Participate in code reviews,



testing, and CI/CD initiatives to improve solution quality and delivery efficiency Support the continuous improvement of data engineering frameworks, standards, and best practices Bachelor's degree in Computer Science, Engineering, Information Technology, Data Analytics, or a related field ~5+ years of experience in Data Engineering, ETL/ELT development, or Big Data environments ~Strong proficiency in Python and SQL ~ Experience building data platforms that support data science and machine learning workloads (Python, Anaconda) ~ Experience developing Spark applications using DataFrames, RDDs, and Spark SQL ~ Experience building and supporting enterprise-scale data pipelines and distributed data processing solutions ~ Experience working with cloud data lakes and data warehouse technologies including Snowflake, Redshift, Delta Lake, S3, or HDFS ~ Strong understanding of data modelling, data warehousing, and modern data architecture principles ~ Experience implementing data quality, validation, and monitoring frameworks ~ Familiarity with Git, version control processes, and CI/CD practices ~ Robust analytical, troubleshooting, and performance optimization skills ~ Experience working in Agile delivery environments ~ Experience with Databricks and Lakehouse architectures Experience with AWS, Azure, or Google Cloud Platform Experience with Kafka, Spark Structured Streaming, or real-time data processing technologies Experience supporting Machine Learning or AI data platforms Industry experience within Financial Services, Retail, Healthcare, Telecommunications,



Manufacturing, or Public Sector organizations Experience with data governance, metadata management, and data catalog solutions Adastra is a global leader in AI and data-driven transformation, helping organizations lead with artificial intelligence—responsibly, strategically, and at scale. With over 25 years of experience, Adastra empowers enterprise clients to unlock business value through data innovation, operational excellence, and smart customer engagement. Trusted by some of the world’s most prominent brands, Adastra delivers end-to-end solutions grounded in thoughtful strategy, robust governance, and deep technical expertise.

From defining vision to ensuring execution, Adastra guides organizations through every stage of their AI, data and cloud journey—building future-ready capabilities and delivering measurable, lasting impact. Adastra serves clients across key industries including financial services, automotive, manufacturing, technology, media and telecom (TMT), healthcare, retail, and qualified services. A flexible, dynamic, and diverse workplace In our commitment to promote fair and equitable treatment of all employees and applicants, Adastra Corporation provides equal employment opportunities for all individuals regardless of age, sex, disability, race, ethnic origin, citizenship, creed, sexual orientation, marital status, or any other ground as described in the Ontario Human Rights Code.In addition, accommodation will be provided during the hiring process.

Adastra

Corporation’s implementation and support of employment initiatives, encourage diversified labour force participation and equal access to opportunities based on merit and performance. AI Usage - Our hiring process includes the use of AI-enabled tools to screen applications (e.g., A human recruiter reviews all AI-generated shortlists to make informed hiring decisions. #

📌 Data Architect Data Analytics (Markham)
🏢 Adastra
📍 Markham