Remote Senior Data Engineer (ETL Data Modeling)
Karnataka, Bengaluru, India
RemoteStar
Hire the best person for the job, no matter where they are. Hire the right way, hire remote.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
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Agile Airflow APIs AWS AWS Glue Big Data Bitbucket CloudFormation Dagster Data governance Data quality Data warehouse DevOps Distributed Systems ELT Engineering ETL Finance Git Kafka Kubernetes Lake Formation Machine Learning ML models Open Source Pipelines PySpark Python RDBMS Redshift Scala Security Snowflake Spark SQL Statistics Streaming Terraform
Perks/benefits: Flex hours Startup environment
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