Cloud Data Engineer

Overview of 66degrees

66degrees is an end-to-end AI transformation partner that guides enterprises from complex business challenges to clear, quantifiable outcomes. Our company is the culmination of several successful firms, each a leader in its own right in cloud, artificial intelligence, and data. This convergence of talent and expertise is how we help businesses reach their own "inflection point," where chaotic data becomes a strategic asset, complexity becomes clarity, and AI becomes an engine for growth. Our ultimate vision is to be the catalyst for a future where every business operates as an intelligent enterprise, with autonomous systems unlocking human potential.

At 66degrees, we believe in thriving through challenges and winning together. These values not only guide us in achieving our goals as a company but also for our people. We are dedicated to creating a significant impact for our employees by fostering a culture that sparks innovation and supports professional and personal growth along the way.

Overview of Role

We are seeking a highly skilled Cloud Data Engineer to join our Managed Services team. In this role, you will be the technical backbone for our enterprise clients, responsible for designing, building, and maintaining high-performance data platforms using Snowflake and Azure Databricks. You will act as a trusted advisor, ensuring that our customers' data ecosystems are scalable, secure, and cost-optimized across multi-cloud environments.

Key Responsibilities

• Platform Engineering: Design and implement end-to-end data lakehouse architectures using Azure Databricks (Delta Lake),Azure HDInsights and Snowflake Cloud Data Warehouse.

• Pipeline Development: Build scalable, metadata-driven ETL/ELT pipelines using Azure Data Factory (ADF), PySpark, and SnowSQL, including ingestion workflows from HDInsight-managed Hadoop and Kafka clusters.

• Managed Services Support: Provide Tier-3 technical support for client environments, including performance tuning, complex bug fixes, and architectural optimizations.

• Multi-Cloud Integration: Oversee data movement and integration strategies across Azure, AWS, and GCP to ensure seamless "Data Everywhere" capabilities for clients.

• Cost & Performance Governance: Monitor and optimize Snowflake credit consumption and Databricks cluster usage to ensure clients receive maximum ROI.

• Security & Compliance: Implement enterprise-grade security including Role-Based Access Control (RBAC), Row-Level Security (RLS), and data masking (Dynamic Data Masking in Snowflake / Unity Catalog in Databricks).

Required Technical Skillset

Category

Must-Have Skills

Snowflake

Snowpipe, Streams & Tasks, Dynamic Tables, Zero-Copy Cloning, and Snowpark (Python/Java), Data Sharing.

Azure Databricks

Spark SQL, PySpark, Delta Lake, Unity Catalog, and Medallion Architecture (Bronze/Silver/Gold)

Orchestration

Azure Data Factory, Airflow, or dbt (Data Build Tool).

Cloud Infrastructure

Azure Data Lake Storage (ADLS Gen2), Azure DevOps (CI/CD), and Terraform/Bicep for IaC.

Languages

Advanced SQL (Window functions, CTEs) and Python.

Experience & Qualifications

• Experience: 5+ years in Data Engineering, with at least 3 years of hands-on experience in both Snowflake and Databricks.

• Managed Services Background: Proven experience supporting external customers with strict SLAs and complex governance requirements.

• Multi-Cloud (Plus): Direct experience deploying Snowflake or Databricks on AWS or GCP is highly desirable.

• Certifications (Preferred): * SnowPro Core or Advanced Architect

• Databricks Certified Data Engineer Professional

• Microsoft Certified: Azure Data Engineer Associate (DP-203)

66degrees is an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to actual or perceived race, color, religion, sex, gender, gender identity, national origin, age, weight, height, marital status, sexual orientation, veteran status, disability status or other legally protected class.