Data Engineer
Data Engineer
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Salary Not Disclosed
1 Vacancy
Job Description
This is a CONTRACT TO POSSIBLE HIRE POSITION!
Were seeking a Mid-Level Data Engineer with hands-on experience in configuring and optimizing Apache Iceberg infrastructure. The role involves building out our foundational Iceberg data lakehouse architecture and integrating it with key cloud and analytics platforms. You will be a core part of our data engineering team working closely with analytics and BI teams to ensure seamless data access and usability.
Key Responsibilities
- Iceberg Infrastructure Configuration
- Design and implement the initial Apache Iceberg infrastructure.
- Ensure compatibility and optimization for batch and streaming data use cases.
- Platform Integration & Connectivity
- Set up and manage connections between Iceberg and:
- Google Cloud Platform (GCP)
- Snowflake With a focus on Federated Data Warehousing (FDW).
- MicroStrategy
- Looker
- Power BI (lower priority but still considered for downstream enablement)
- Set up and manage connections between Iceberg and:
- Data Pipeline Development
- Build and deploy initial pipelines for data flow from:
- Snowflake Iceberg MicroStrategy
- Monitor and optimize data ingestion transformation and delivery.
- Ensure data quality lineage and security compliance throughout the pipeline.
- Build and deploy initial pipelines for data flow from:
- Collaboration & Documentation
- Collaborate cross-functionally with data science analytics and DevOps teams.
- Document configuration design patterns and integration processes.
Qualifications :
Required:
- 35 years of experience in data engineering or related field.
- Proven experience configuring and managing Apache Iceberg environments.
- Hands-on experience with Snowflake including familiarity with FDW.
- Experience integrating cloud storage systems and query engines (e.g. BigQuery GCP).
- Working knowledge of BI tools: MicroStrategy Looker Power BI.
- Proficiency in Python SQL and data orchestration tools (e.g. Airflow).
- Strong understanding of data lakehouse architecture and performance optimization.
Preferred:
- Familiarity with secure data sharing and access control across tools.
- Knowledge of metadata catalogs such as Apache Hive AWS Glue or Unity Catalog.
- Background in working with distributed data systems and cloud-native environments.
Remote Work :
Yes
Employment Type :
Full-time
Employment Type
Remote
Company Industry
Key Skills
- Apache Hive
- S3
- Hadoop
- Redshift
- Spark
- AWS
- Apache Pig
- NoSQL
- Big Data
- Data Warehouse
- Kafka
- Scala
