Lead Data Engineer

Candidate should have :

Worked collaboratively with cross-functional teams and stakeholders to achieve an organizational goal.

Worked in an agile environment and are comfortable running an agile process for the data and analytics team.

Strong experience in data pipelines, ETL design (both implementation and maintenance), data warehousing, and data modeling (preferably in dbt).

Implementation and tuning experience in the Big Data Ecosystem,

(such as Data Analytics (Dataproc, Airflow, Hadoop, Spark, Hive),

Google Cloud Platform AI and ML Services and Data Warehousing (such as BigQuery, schema design,

query tuning and optimization) and data migration and integration.

End to end hands-on to carry out complex POC, Pilot, Limited production rollout, assignments requiring the development of new or improved techniques and procedures.

Participated in deep architectural discussions to build confidence and ensure customer, success when building new, or migrating existing, applications, software, and services on the Google Cloud Platform.

advanced skills in SQL, data modeling, ETL / ELT development, and data warehousing.

Strong skills in Optimization - performance, pipeline, spark.

Experience on Pyspark.

5+ years of design & implementation experience with distributed applications.

5+ years of experience architecting / operating solutions built on Google Cloud Platform.

• Bachelor’s degree.