Data Engineer

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.