Description

You design and implement data engineering solutions on Google Cloud Platform, owning the full lifecycle from ingestion to analytics.

This role is on-site.

Responsibilities

• Build data ingestion pipelines for heterogeneous sources using batch and real-time processing.
• Develop components for data analytics, search, and aggregation.
• Implement data integration, transformation, and storage frameworks.
• Optimize data pipelines and computation frameworks for performance and reliability.
• Drive design discussions to ensure the health and performance of the overall data solution.

Required Skills

• 6 to 8 years of professional experience in data engineering.
• Minimum 3 years of hands-on experience with Big Data technologies.
• Strong proficiency in Java, Scala, or Python (Java preferred).
• Hands-on experience with the Hadoop stack: HDFS, Sqoop, Kafka, Pulsar, NiFi, Spark, Spark Streaming, Flink, Storm, Hive, Oozie, Airflow.
• Experience with NoSQL and MPP platforms: HBase, MongoDB, Cassandra, AWS Redshift, Azure SQLDW, or GCP BigQuery.
• Working knowledge of real-time data pipelines and AWS data platform services.

Preferred Skills

• Experience with traditional ETL tools (Informatica, Talend) and relational databases (Oracle, MySQL, SQL Server, Postgres).
• Knowledge of data governance processes and tools like Collibra or Alation.

Key Skills

Education

Any Graduate