Position Name – Data Engineer
Type of hiring – Fulltime/Subcon
Location – Calgary, AB (Onsite Hybrid)
Job Description:
We are seeking a skilled Data Engineer to design, develop, and maintain scalable data pipelines and infrastructure that support data-driven decision-making.
The ideal candidate will have strong experience in data integration, data modeling, ETL/ELT processes, cloud data platforms, and data quality management, with the ability to collaborate with cross-functional teams to deliver reliable and high-performing data solutions.
Key Responsibilities
- Collect, integrate, clean, and pre-process structured and unstructured data from multiple sources.
- Design, develop, and maintain scalable data pipelines and ETL/ELT workflows.
- Build and optimize data models, data warehouses, and data lakes to support analytics and reporting requirements.
- Perform exploratory data analysis (EDA) to identify trends, patterns, anomalies, and data quality issues.
- Develop and maintain data integration solutions using SQL, Python, and relevant data engineering technologies.
- Implement data validation, monitoring, and quality checks to ensure data accuracy, consistency, integrity, and reliability.
- Optimize data pipelines and database queries for performance, scalability, and cost efficiency.
- Collaborate with data scientists, analysts, business stakeholders, product teams, and software engineers to translate business requirements into effective data solutions.
- Support the development and deployment of machine learning and predictive analytics solutions by preparing reliable, high-quality datasets.
- Build and maintain dashboards, reports, and data visualizations to communicate business insights where required.
- Implement data governance, security, access controls, and compliance standards in accordance with organizational policies.
- Monitor pipeline performance, troubleshoot data processing issues, and implement continuous improvements.
- Work with cloud-based data platforms and modern data engineering tools to support enterprise data initiatives.
- Explore and adopt emerging technologies in data engineering, analytics, artificial intelligence, machine learning, and Generative AI.
Required Qualifications
- Bachelor's Degree in Computer Science, Information Technology, Data Engineering, Software Engineering, or a related field.
- Proven experience in data engineering, data integration, or a similar technical role.
- Strong proficiency in SQL and Python for data processing, transformation, and automation.
- Hands-on experience building and maintaining ETL/ELT pipelines and data integration workflows.
- Experience with relational databases, data warehousing, and data modeling concepts.
- Familiarity with cloud platforms such as Microsoft Azure, AWS, or Google Cloud Platform.
- Experience with data processing frameworks and technologies such as Apache Spark, Databricks, or similar platforms.
- Strong understanding of data quality, data governance, metadata management, and data security principles.
- Experience with version control, automated testing, and CI/CD practices for data pipelines.
- Excellent analytical, problem-solving, communication, and collaboration skills.
Preferred Qualifications
- Experience with cloud-based data lakehouse architectures and modern analytics platforms.
- Familiarity with orchestration tools such as Apache Airflow, Azure Data Factory, or similar technologies.
- Experience with streaming data platforms such as Apache Kafka or equivalent technologies.
- Knowledge of business intelligence tools such as Power BI or Tableau.
- Exposure to statistical analysis, hypothesis testing, A/B testing, and predictive modeling.
- Familiarity with machine learning workflows and Generative AI applications.
- Experience working in the energy, utilities, oil and gas, or other large enterprise environments is an asset.
