Description

You will architect and implement data pipelines to process large datasets from databases, APIs, and web services.

This role is on-site.

Responsibilities

• Architect data pipelines to move data from various sources into data lakes or warehouses.
• Build scalable data processing solutions using Snowflake, AWS, and GCP.
• Develop data quality checks and monitoring systems to ensure accuracy throughout the pipeline.
• Implement Machine Learning algorithms for anomaly detection, data quality, and continuous monitoring.
• Contribute to data governance, including lineage tracking, access controls, and retention policies.

Required Skills

• 7+ years of experience with data warehouse architectures, ETL/ELT, and scripting.
• 5+ years of data modeling experience with advanced SQL and query performance tuning.
• Proficiency in Python and SQL for data manipulation and processing.
• Experience with Snowflake, including multi-cluster architecture and shareable data features.
• Hands-on experience with AWS services including S3, Lambda, and Data-pipeline.
• Working knowledge of BigQuery, Databricks, and GCP.
• Experience with Apache Airflow or AWS MWAA.
• Familiarity with CI/CD pipelines and automation tools.

Preferred Skills

• Expertise in distributed processing frameworks like Apache Spark.
• Experience with ETL tools such as Databricks or IBM DataStage.

Key Skills

Education

Bachelor's degree