Job Description
Lead day-to-day operations to ensure organizational delivery of quality results.
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- Responsible for provisioning, enabling, scaling and maintaining our team’s data, analytics and ML infrastructures for batch and real time systems including pipelines, frameworks, tools and services in hybrid cloud.
- Shepherd zero-downtime deployment process through continuous delivery practices, rapidly releasing features that provide critical and faster insights to business users.
- Collaborate with the platform team by building the right tools for observability , monitoring, alerting and self-healing for the day to day management of analytics foundations.
- Debug complex problems in distributed environment and ability to run the prod incidents efficiently to following up with Post incident reviews.
- Developing self-service tools and automation to improve engineering efficiency and the quality of services.
- Excellent verbal and written communication skills.
- Self-starter with forward thinking capability with strong executional track record and be accountable for business priorities.
- Hands-on experience with CI/CD pipelines and cloud environments like Gitlab, Spinnaker, Docker/Kubernetes observability using Splunk, Grafana/Data dog is a huge plus.
- Proficient with one or more programming languages such as Python/Go/Rust/Java/Scala for automation and API integrations.
- Experience in implementing security controls, governance processes, compliance validation, infrastructure cost analysis and optimization.
- Knowledge of analytics and Applied ML stack like Apache Spark, Trino/Pinot, Iceberg, Atlas, Flink, Airflow/Luigi, Tableau, Snowflake, Databricks, MLFlow, Data Catalogs, Jupyter Notebooks, Vector database and Cassandra.
- Solid understanding of IAAC (infrastructure as a code) techniques like terraform, orchestration and tooling.
- Experience scaling operations in a fast-paced and dynamic environment. Experience working in agile or evolving product environments.?
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