Senior Data Engineer

The Senior Data Engineer is responsible for designing, developing, and maintaining scalable data pipelines and models within Snowflake and cloud environments. This role combines strong SQL and Python development with hands-on data engineering in Agile teams. The engineer will partner with architects, analysts, and business teams to deliver secure, reliable, high-quality data solutions that power analytics, reporting, and operational workflows.

Responsibilities:

Design, build, and optimise SQL pipelines, transformations, and data models within Snowflake.

Develop Python-based data processing, automation, and integration workflows.

Ingest and process structured, semi-structured, and unstructured data from databases, APIs, files, SaaS applications, and cloud storage.

Implement ETL/ELT processes using SQL, Python, dbt, Snowflake features, or orchestration tools such as Airflow/Dagster.

Contribute to Agile ceremonies and deliverables, ensuring timely and high-quality sprint outcomes.

Implement CI/CD workflows and maintain version-controlled repositories (GitHub or equivalent).

Support data governance, data quality, and secure data handling practices.

Troubleshoot pipeline issues and proactively drive performance improvements.

Maintain documentation, monitoring, alerting, and operational playbooks for pipelines.

Requirements:

Ability to work effectively within cross-functional and Agile teams.

Strong analytical, problem-solving, and critical-thinking skills.

Experience working with US- and Europe-based clients, stakeholders, or team members is desired.

Clear written and verbal communication skills, including the ability to translate technical information for non-technical partners.

Strong organisational skills with attention to detail and documentation.

Ability to influence and collaborate across teams and geographies.

Demonstrated ownership, adaptability, and willingness to embrace new technologies.

Ability to understand and work across multiple technology stacks.

Good to Have:

7 + years of experience designing and developing SQL-based pipelines and data models.

Hands-on experience with Python for ETL/ELT development and automation.

Experience with Snowflake or other cloud data warehouses.

Experience with orchestration platforms such as Airflow, Dagster, or Prefect.

Experience with ingestion tools (Fivetran, Airbyte) is a plus.

Familiarity with APIs, JSON/CSV/XML/Parquet data formats, and cloud storage environments.

Understanding of CDC mechanisms, data governance, and security best practices.

Exposure to real-time or streaming ingestion (Kafka, Event Hub) is beneficial.

Experience working in Agile environments and delivering iterative outcomes.

Ability to participate in and lead technical discussions.

Interest or exposure to AI/ML workflows is a plus.

Must-have skills (Mandatory) - Data Engineering, Data Modelling, ETL/ELT, SQL, Snowflake, AWS OR Azure.

Good-to-have skills (Preferred) - Python, Data governance, AI Cortex Agent, Airflow OR Dagster.

Technologies Required:

SQL (strong expertise), Snowflake is a plus, and data modelling.

Python for data pipelines and automation.

dbt / SQL-based transformation frameworks.

Airflow, Dagster, or similar orchestration tools.

CI/CD tools (GitHub, GitLab, Azure DevOps).

ETL/ELT tools such as Fivetran, Airbyte, Apache NiFi.

Cloud services (AWS, Azure, GCP) and cloud storage.

Git-based version control.