Senior DevOps Engineer, IT - Data Operations Engineering

Edwards Lifesciences is expanding its global technology capabilities with the launch of a new IT Innovation Hub in Pune, India. The Hub strengthens the technology foundation that supports our business worldwide, working in close partnership with teams across regions to deliver reliable, high-quality solutions at scale.

Designed as a long-term investment, the Pune Hub will advance newer digital capabilities such as automation, data, AI, and cloud, and will include roles spanning end user services, application development, and enterprise platform teams.

As part of our IT team, your   expertise   and commitment will help build and   operate   the platforms that power Edwards' global data and analytics solutions. We are seeking a Senior DevOps Engineer to support Data Operations Engineering and own the operational backbone of our data platforms, including infrastructure as code, continuous integration and delivery, data quality monitoring and incident response, observability, security operations, and cloud cost optimization. Our multi-cloud estate includes Databrick s and Snowflake, with data services moving to Azure while AWS continues to host corporate source systems.

How you will make an impact

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Build and   maintain   modular Terraform components that provision cloud and Databricks platform capabilities, including workspaces, cluster policies, secret scopes, networking, and Unity Catalog storage credentials and external locations, consistently across environments and clouds.

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Design and   operate   automated GitLab CI/CD pipelines that deploy data platform code and infrastructure through development, staging, and production with approval gates and controlled promotion.

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Monitor data quality and pipeline health, own first-line response to production alerts, resolve issues directly where possible, and escalate only when the root cause requires deeper pipeline or platform change.

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Build, test, and continuously improve runbooks for recurring failure modes, automating remediation when the response can be made safe and repeatable.

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Apply AI- and agent-assisted operations capabilities to accelerate detection, triage, and remediation as those capabilities mature.

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Build end-to-end observability across Databricks, Snowflake, and orchestration services by bringing platform and execution metadata into unified dashboards, alerting, and pipeline service-level monitoring.

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Containerize and   operate   platform workloads, orchestration, and CI runners on Docker and Kubernetes across EKS and AKS.

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Operate and re-host Apache Airflow,   consolidating   self-managed instances onto Kubernetes or a managed runtime, while supporting migration of legacy build tooling to GitLab CI.

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Embed security operations into the platform lifecycle through   secrets   management, short-lived credentials, least-privilege access, encryption key policies, audit logging, and vulnerability remediation.

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Drive cloud cost optimization through cost attribution, policy enforcement, right-sizing, tagging standards, and anomaly alerting.

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Support secure cross-cloud connectivity and data movement between AWS-resident source systems and the Azure data platform.

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Identify   opportunities for automation, reusable standards, reliability improvement, and technical debt reduction, and   provide   technical guidance to team members.

What you will need (Required)

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Bachelor's Degree in Computer Science , Engineering, Information Technology, or a related field and a minimum of 5 years of relevant experience in DevOps, platform engineering, site reliability engineering, or cloud infrastructure roles.

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Strong hands-on experience administering and automating workloads on both Amazon Web Services and Microsoft Azure, including identity, networking, and storage services.

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Demonstrated   expertise   building modular, reusable infrastructure with Terraform across multiple environments.

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Proven experience designing and   maintaining   CI/CD pipelines in GitLab CI or an equivalent platform, including environment promotion, approval gates, and   secrets   handling.

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Strong   proficiency   with Docker and Kubernetes, including EKS or AKS and running CI/CD or orchestration workloads on Kubernetes.

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Hands-on experience operating Apache Airflow, including DAG deployment, scheduling, retries, backfills, pools, and failure recovery.

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Solid Linux systems administration, shell scripting, and troubleshooting skills.

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Hands-on experience implementing metrics, logging, dashboards, and alerting using tools such as Datadog or Grafana.

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Demonstrated experience monitoring pipeline and data quality, owning first-line triage of production alerts, and writing and executing runbooks for recurring failures.

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Working knowledge of   secrets   management, least-privilege access control, encryption key management, audit logging, and vulnerability remediation.

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Working knowledge of cloud cost monitoring, attribution, tagging standards, and right-sizing practices.

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Proficiency   in Python or another scripting language used for automation and tooling.

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Excellent analytical, troubleshooting, communication, and organizational skills with the ability to work across cross-functional and geographically distributed teams.

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Ability to manage competing priorities in a fast-paced environment while   maintaining   attention to quality, controls, and long-term outcomes.

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Adhere to all company rules and requirements, including Environmental Health & Safety rules, and take adequate control measures to prevent injuries, protect the environment, and prevent pollution under their span of influence or control.

What else we look for (Preferred)

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Experience operating Databricks or Snowflake, including platform administration, policy management, and service principal or access management.

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Experience with Databricks Asset Bundles, Unity Catalog, the Databricks Terraform provider, or managed Terraform state and gated production applies.

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Experience with keyless authentication from CI, such as OIDC-based role assumption or IRSA.

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Experience with data observability or AI-assisted operations capabilities, such as Monte Carlo, Datadog AI capabilities, or Databricks operations automation.

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Experience with Astronomer, MWAA, or Airflow on Kubernetes using   KubernetesExecutor .

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Experience with Azure Data Factory, ADLS Gen2, Key Vault, Azure Monitor, and Entra ID, or AWS Glue, Athena, Lambda, and Secrets Manager.

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Experience supporting hybrid or cross-cloud architectures and private connectivity among clouds and on-premises environments.

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Experience migrating CI/CD from Jenkins or another legacy build platform.

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Experience with   streaming or   change   data capture technologies such as AWS DMS, Amazon MSK, or Kafka.

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Experience with SALT, Ansible, Azure DevOps, or related configuration and delivery tooling.

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Relevant experience in medical   device , pharmaceuticals, or another highly regulated environment, including validation and change control expectations.

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Relevant AWS, Azure, Kubernetes, or Terraform certifications.

Additional   information

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Develops solutions to a variety of complex platform and operational problems and exercises judgment in selecting methods and techniques after considering risk and alternatives.

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Works with general direction focused on end results and may   provide   technical guidance to lower-level personnel.

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Participation in an on-call rotation may be   required   to support platform reliability.

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Travel may be   required   up to 5%.

Benefits and equal opportunity

Aligning our overall business   objectives   with performance, we offer competitive salaries, performance-based incentives, and a wide variety of benefits programs to address the diverse individual needs of our employees and their families.

Edwards, Edwards Lifesciences, and the stylized E logo are trademarks of Edwards Lifesciences Corporation or its affiliates. All other trademarks are