Senior Data Engineer – ETL Data Modeling

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🕒 March 31

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RemoteStar

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2020

🤝 B2B

🎯 Recruiter

☁️ SaaS

B2B • Recruitment • SaaS

RemoteStar is a global recruitment service that specializes in hiring top-quality tech talent. By assembling diverse teams with vetted developers from various regions, RemoteStar ensures high-quality staffing while maximizing cost efficiency for companies. The service includes a rigorous vetting process, technical matching, and full onboarding support, allowing businesses to focus on their core operations while RemoteStar handles the administrative aspects of recruitment and team management.

📋 Description

• 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.

🎯 Requirements

• 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

🏖️ Benefits

• 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