Description

You will design and lead end-to-end data solutions, defining platform patterns for batch and streaming data flows, ingestion, storage, and processing.

This role is on-site.

Responsibilities

• Build scalable data pipelines and prototypes using modern data stack technologies.
• Optimize data performance, partitioning, and query efficiency across cloud data warehouses.
• Establish CI/CD practices, reusable frameworks, and standards for data engineering teams.
• Ensure security, governance, and compliance through IAM, encryption, and data quality controls.
• Drive observability, monitoring, and cost optimization for enterprise-scale data platforms.

Required Skills

• 6+ years in Data Engineering or Data Architecture with hands-on experience building enterprise-scale data pipelines.
• Strong expertise in data modeling (Dimensional, Data Vault, schema design).
• Proficiency with cloud data warehouses: Snowflake, Redshift, or BigQuery.
• Experience with processing frameworks: Spark, Databricks, or PySpark.
• Streaming experience with Kafka or Kinesis.
• Strong programming in Python or Scala and advanced SQL skills.
• Hands-on experience with ETL/ELT and orchestration tools like Airflow or dbt.
• AWS cloud platform experience with knowledge of IAM, encryption, and data security best practices.
• Strong stakeholder communication and architecture decision-making skills.

Preferred Skills

• Experience with infrastructure as code and containerization: Terraform, Kubernetes, Docker.
• Familiarity with data governance tools for lineage, cataloging, and data quality.
• AWS Architect, Databricks, Snowflake, or CDMP certifications.

Key Skills

Education

Any Gradute