Job Description
RemoteStar is looking to hire a Remote Senior Data Engineer (ETL Data Modeling) on behalf of our client based in the UK with a fully remote work policy.
About Client:
The client building, the B2B marketplace for diamonds. It’s an industry-leading B2B diamond and gemstones marketplace, connecting jewellery retailers to gemstone supplies They have a presence in London, Hong Kong, Amsterdam, and as well in Mumbai and now in New York in 2001.
About the role
The Remote Senior Data Engineer (ETL Data Modeling) plays a pivotal role in growing our externally facing technical platform, supporting our customers' needs, and driving technical excellence within the team.
RESPONSIBILITIES:
- Implementing ETL/ELT pipelines within and outside of a data warehouse using Python, Pyspark and Snowflakes Snow SQL.
- Support Redshift DWH to Snowflake Migration.
- Design, implement, and support data warehouse/data lake infrastructure using AWS big data stack, Python, Redshift, Snowflake, Glue/lake formation, EMR/Spark/Scala etc.
- Work with data analysts to scale value-creating capabilities, including data integrations and transformations, model features, and statistical and machine learning models.
- Work with Product Managers, Finance, Service Engineering Teams and Sales Teams on a day-to-day basis to support their new analytics requirements.
- Implement data quality and data governance measures and execute data profiling and data validation procedures
- Implement and uphold data governance practices to maintain data quality, integrity, and security throughout the data lifecycle.
- Leverage open-source technologies to build robust and cost-effective data solutions.
- Develop and maintain streaming pipelines using technologies like Apache Kafka etc.
Skills and
Qualifications:
- Must have total 5+ yrs. of IT experience and 3+ years' experience in data Integration, ETL/ETL development, and database design or Data Warehouse design
- Broad expertise and experience with distributed systems, streaming systems, and data engineering tools, such as Kubernetes, Kafka, Airflow, Dagster, etc.
- Experience in data transformation, ETL/ELT tool and technologies such as AWS Glue, DBTetc for transforming structured/semi structured and unstructured datasets.Experience in ingesting and integrating data from APIs/JDBC/CDC sources.
- Deep knowledge of Python, SQL, relational/ non-relational database design, and master data strategies.
- Experience defining, architecting, and rolling out data products, including ownership of data products through their entire lifecycle.
- Deep understanding of Star and Snowflake dimensional modeling. Experience with relational databases, including SQL queries, database definition, and schema design.
- Experience with data warehouses, distributed data platforms, and data lakes.
- Strong proficiency in SQL and at least one programming language (e.g., Python,Scala, JS).
- Familiarity with data orchestration tools, such as Apache Airflow, and the ability to design and manage complex data workflows.
- Familiarity with agile methodologies, sprint planning, and retrospectives.
- Proficiency with version control systems, Bitbucket/Git.
- Ability to work in a fast-paced startup environment and adapt to changing requirements with several ongoing concurrent projects.
- Excellent verbal and written communication skills.
Preferred/bonus skills:
- Redshift to Snowflake migration experience.
- Experience with DevOps technologies such as Terraform, CloudFormation, and Kubernetes.
- While not mandatory, experience or knowledge in machine learning techniques is highly preferable, enriching our data engineering capabilities.
- Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases
WHAT THEY OFFER
- Dynamic working environment in an extremely fast-growing company
- Work in an international environment
- Work in a pleasant environment with very little hierarchy
- Intellectually challenging, play a massive role in client’s success and scalability
- Flexible working hours
