As a Senior Data Engineer, you will be responsible for the development of complex data sources and pipelines into our data platform (i.e. Snowflake) along with other data applications (i.e. Azure, Airflow, etc.) and automation.
The Senior Data Engineer will work closely with the data, Architecture, Business Analyst, Data Stewards to integrate and align requirements, specifications and constraints of each element of the requirement. They will also need to help identify gaps in resources, technology, or capabilities required, and work with the data engineering team to identify and implement solutions where appropriate.
Work type: Contract
Length: initial 6 months
Work structure: hybrid 2 days a week in London.
Primary Responsibilities:
Integrate data from multiple on prem and cloud sources and systems. Handle data ingestion, transformation, and consolidation to create a unified and reliable data foundation for analysis and reporting.
Develop data transformation routines to clean, normalize, and aggregate data. Apply data processing techniques to handle complex data structures, handle missing or inconsistent data, and prepare the data for analysis, reporting, or machine learning tasks.
Implement data de-identification/data masking in line with company standards.
Monitor data pipelines and data systems to detect and resolve issues promptly.
Develop monitoring tools to automate error handling mechanisms to ensure data integrity and system reliability.
Utilize data quality tools like Great Expectations or Soda to ensure the accuracy, reliability, and integrity of data throughout its lifecycle.
Create & maintain data pipelines using Airflow & Snowflake as primary tools
Create SQL Stored procs to perform complex transformation
Understand data requirements and design optimal pipelines to fulfil the use-cases
Creating logical & physical data models to ensure data integrity is maintained
CI CD pipeline creation & automation using GIT & GIT Actions
Tuning and optimizing data processes
Qualifications
Required Qualifications:
· Bachelor's degree in Computer Science or a related field.
· Proven hands-on experience as a Data Engineer.
· Proficiency in SQL (any flavor), with experience using Window functions and advanced features.
· Excellent communication skills.
· Strong knowledge of Python.
· Familiarity with Azure Services such as Blobs, Functions, Azure Data Factory, Service Principal, Containers, Key Vault, etc.
· In-depth knowledge of Snowflake architecture, features, and best practices.
· Experience with CI/CD pipelines using Git and Git Actions.
· Knowledge of various data modeling techniques, including Star Schema, Dimensional models, and Data Vault.
· Hands-on experience with:
· Developing data pipelines (Snowflake), writing complex SQL queries.
· Building ETL/ELT/data pipelines.
· Kubernetes and Linux containers (e.g., Docker).
· Related/complementary open-source software platforms and languages (e.g., Scala, Python, Java, Linux).
· Experience with both relational (RDBMS) and non-relational databases.
· Analytical and problem-solving skills applied to big data datasets.
· Experience working on projects with agile/scrum methodologies and high-performing teams.
· Good understanding of access control, data masking, and row access policies.
· Exposure to DevOps methodology.
· Knowledge of data warehousing principles, architecture, and implementation.
