We are looking for an experienced Data Engineer with a strong background in data engineering, storage, and cloud technologies. The role involves designing, building, and optimizing scalable data pipelines, ETL/ELT workflows, and data models for efficient analytics and reporting. The ideal candidate must have strong SQL expertise and hands-on experience with cloud platforms, particularly Google Cloud Platform (GCP).
Key Responsibilities
- Design, build, and optimize scalable data pipelines.
- Develop and manage ETL/ELT workflows and data models.
- Write complex SQL queries, including joins, stored procedures, and certificate-auth-based queries.
- Work with NoSQL databases such as Firestore, DynamoDB, or MongoDB.
- Develop and maintain data models and warehousing solutions using platforms like BigQuery (preferred), Redshift, or Snowflake.
- Build and manage ETL/ELT pipelines using tools like Airflow, dbt, Kafka, or Spark.
- Use scripting languages such as PySpark, Python, or Scala to create data processing jobs.
- Collaborate with data analysts and other teams to support their data needs.
Required Skills
- Strong SQL expertise.
- Experience with NoSQL databases (Firestore, DynamoDB, or MongoDB).
- Proficiency in data modeling and data warehousing solutions (BigQuery, Redshift, or Snowflake).
- Hands-on experience with ETL/ELT pipelines and orchestration tools (Airflow, dbt, Kafka, or Spark).
- Proficiency in PySpark, Python, or Scala.
- Strong hands-on experience with Google Cloud Platform (GCP).
Good-to-Have Skills
- Experience with visualization tools like Google Looker Studio, LookerML, Power BI, or Tableau.
- Exposure to Master Data Management (MDM) systems.
- Interest in Web3 data and blockchain analytics.
