Snowflake Data Engineer - Ad

At Apple, everything begins with the customer experience. Apple Ads extends this philosophy to advertising—helping people discover what they need while empowering advertisers to grow their businesses.

Our technology delivers ads and sponsorships across Apple Services, including the App Store, Apple News, and MLS (Major League Soccer) Season Pass. Every solution we build is rooted in trust, connection, and impact: respecting user privacy, integrating advertising seamlessly into the Apple experience, and delivering value for advertisers of every size—from small app developers to global brands. When advertising is done right, it benefits everyone.

Apple Ads, India is seeking Cloud database warehouse engineer (Snowflake) to join the Reliability Engineering Team in Hyderabad, to build, operate, and automate our database platform.

Description

In this role, you’ll work primarily with Snowflake on AWS, alongside open-format lakehouse technologies like Apache Iceberg, and grow your skills in cloud infrastructure, CI/CD, and automation. This is a hands-on role for someone who enjoys scripting away toil, learning cloud-native tooling, and partnering with engineering teams. You’ll be mentored by senior engineers while taking increasing ownership of real production data platforms.

Minimum Qualifications

5-8 years of experience for ICT3 in IT / software / database / data engineering Hands-on experience with Snowflake (or another cloud data warehouse such as Redshift, BigQuery, or Databricks with a clear path to Snowflake); solid understanding of core database and data-warehousing concepts. Strong working knowledge of SQL and fundamentals of query tuning and execution plans (e.g., reading query profiles, clustering/pruning basics, warehouse sizing, and Account Usage / Information Schema views). Experience with at least one major cloud provider, ideally AWS, and its core services (compute, managed storage such as S3, networking, security groups, VPC, PrivateLink, KMS, IAM). Proficiency in Python for scripting and automation (Snowpark Python a plus). Exposure to CI/CD and DevOps tooling (e.g., Git, Jenkins/GitLab CI/GitHub Actions, and infrastructure-as-code such as Terraform or CloudFormation, Helm, ArgoCD, ACK). Exposure to open-format lakehouse technologies such as Apache Iceberg (a plus). A demonstrated bias toward automation — a track record of scripting or automating repetitive work. Working knowledge of Linux/Unix fundamentals. Strong analytical and problem-solving skills, eagerness to learn, and good communication and collaboration skills.

Preferred Qualifications

Exposure to GenAI application building, MCP and prompt engineering Experience with Streamlit, Snowpark Python / Snowpark pandas for in-database transformations. Hands-on with Apache Iceberg tables, external volumes, and open-format lakehouse patterns. Familiarity with AWS networking and connectivity — PrivateLink, VPC peering, gateways, and load balancing. Experience building and orchestrating data pipelines (e.g., dbt, Airflow, Dagster, or Snowflake Tasks & Streams). Exposure to observability and monitoring stacks (e.g., Datadog, Prometheus/Grafana, Splunk).