Senior Data Engineer

About the Role

This position is for an experienced Senior Data Engineer who will shape, build, and support scalable data platforms and pipelines that enable analytics, reporting, and informed business decisions across the company. The role calls for deep hands-on expertise with SQL, Python, DBT, Fivetran, Airflow, and Snowflake, plus a strong background in modern cloud data architecture and workflow optimization.

You will work closely with Data Analysts, Analytics Engineers, Data Scientists, and internal stakeholders to keep data dependable, accessible, and of high quality for the wider organization.

Responsibilities

• Develop, enhance, and support scalable ELT and ETL workflows using Python, Fivetran, DBT, and Apache Airflow.
• Create and tune Snowflake data models that power reporting, analytics, and business intelligence use cases.
• Build DBT models that are reusable, clearly documented, tested, and easy to maintain.
• Track pipeline health and continuously improve reliability, speed, and scalability.
• Put in place data validation rules, quality controls, and automated testing practices.
• Own orchestration and scheduling activities through Airflow.
• Work with business and technical teams to interpret data needs and turn them into scalable solutions.
• Design and support data warehouse structures with strong attention to governance, security, and performance.
• Investigate data issues and recommend process improvements before problems recur.
• Guide junior engineers and help define engineering standards and best practices.
• Take part in architecture reviews and technology assessments that shape the data platform’s future.

Requirements

• At least 5 years of experience in data engineering, analytics engineering, or a closely related role.
• Advanced SQL ability, including tuning complex queries and handling very large datasets.
• Strong Python skills for automation and data processing tasks.
• Practical DBT experience covering modeling, testing, documentation, and deployment.
• Experience building and managing ingestion pipelines with Fivetran or comparable ELT tools.
• Solid working knowledge of Apache Airflow for orchestration.
• Strong Snowflake knowledge, including architecture, performance tuning, and warehouse design.
• Experience working with cloud-based data platforms and modern data stack tools.
• Good understanding of data warehousing, dimensional modeling, and ELT best practices.
• Experience with Git-based version control and CI/CD workflows.
• Strong problem-solving, communication, and cross-functional collaboration skills.
• Bonus exposure to AWS, Azure, or Google Cloud Platform.
• Familiarity with data governance, lineage, and metadata management tools is preferred.
• Experience supporting BI tools such as Tableau, Power BI, or Looker is preferred.
• Knowledge of Infrastructure as Code tools such as Terraform is preferred.
• Exposure to streaming or near real-time pipelines is preferred.
• Experience in Agile or Scrum environments is preferred.

Perks

• Work on a modern cloud-native data platform.
• Join a collaborative, data-led team culture.
• Access career growth and leadership opportunities.
• Receive a competitive compensation and benefits package.

Success Metrics

• Data pipelines remain dependable, scalable, and easy to maintain.
• Analytics platforms consistently reflect accurate and trusted data.
• Pipeline failures are reduced and day-to-day operations become more efficient.
• Data solutions are delivered in time to support business decisions.
• Engineering, analytics, and business teams work together effectively.

Technical Stack

SQL, Python, DBT, Fivetran, Apache Airflow, Snowflake, Git, and cloud platforms such as AWS, Azure, or GCP.

Additional Information

By submitting an application, the candidate agrees that their personal information may be collected, processed, and retained by the company only for recruiting and evaluation purposes.