We are looking for an experienced Data Engineer with a solid background in data engineering, cloud storage, and modern data platforms. The ideal candidate will be responsible for building scalable data pipelines, ETL/ELT workflows, and data models to support high-quality analytics and reporting.
Key Responsibilities:
- Design, develop, and optimize scalable data pipelines and ETL/ELT workflows.
- Build robust data models to support business intelligence and advanced analytics.
- Work with structured and unstructured data across a range of databases and storage solutions.
- Collaborate with analytics, product, and engineering teams to support data needs across the organization.
- Ensure data quality, performance, and governance across the pipeline lifecycle.
Required Skills and Experience:
- Strong expertise in SQL, including complex joins, stored procedures, and certificate-authenticated queries.
- Experience with NoSQL databases such as:
- Firestore
- DynamoDB
- MongoDB
- Proficiency in data warehousing and data modeling using platforms such as:
- BigQuery (preferred)
- Redshift
- Snowflake
- Hands-on experience with ETL/ELT tools and frameworks, including:
- Apache Airflow
- dbt
- Kafka
- Apache Spark
- Proficiency in Python, PySpark, or Scala for data transformation and automation.
- Strong practical knowledge of Google Cloud Platform (GCP) and its native services.
Preferred Skills:
- Experience with data visualization tools:
- Google Looker Studio
- LookerML
- Power BI
- Tableau
- Exposure to Master Data Management (MDM) systems.
- Interest or experience in Web3 data and blockchain analytics.
