Description

You will lead large-scale data engagements on cloud platforms, focusing on data lakes, migration, warehousing, and business intelligence.

Responsibilities

• Lead multiple data engagements on GCP, focusing on data engineering, migration, and warehouse implementation.
• Design and develop distributed, high-volume multi-thread batch, real-time, and event processing systems.
• Translate business requirements into functional and non-functional specifications including scalability, security, and resilience.
• Partner with pre-sales teams to support RFPs and RFIs by creating technical solutions and statements of work.
• Implement processes to validate data and monitor quality to ensure accuracy for business stakeholders.
• Mentor junior talent and act as a technical advisor for complex cloud and data challenges.

Required Skills

• 15+ years of experience in technical, solutioning, and analytical roles.
• 5+ years of experience building and managing Data Lakes, Data Warehouses, and Data Integration solutions on GCP, AWS, or Azure.
• Expertise in designing end-to-end data pipelines for structured and unstructured data sources.
• Proficiency with distributed computing in Hadoop and cloud environments.
• Hands-on experience with Spark, PySpark, Scala, Dataflow, Dataproc, and EMR.
• Experience with traditional ETL tools such as Informatica, DataStage, OWB, or Talend.
• Deep knowledge of databases including Oracle, Teradata, MySQL, DB2, and SQL Server.
• Experience with NoSQL databases such as MongoDB, Cassandra, or CouchDB.
• Ability to architect scalable cloud data warehouses using BigQuery or Redshift.
• Knowledge of data orchestration and streaming tools like Airflow, Kafka, Pub/Sub, or Kinesis.
• Understanding of IaaS, PaaS, SaaS, containers, and microservices architecture.
• Experience with BI reporting tools such as Looker, Tableau, or Power BI.

Preferred Skills

• Experience with Machine Learning frameworks like TensorFlow or PyTorch.

Key Skills

Education

Not specified