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Senior Data Platform Engineer

Remote Senior Contract Posted

Summary

Written in English from the original posting

Lifted is seeking a Senior Data Platform Engineer for a remote contract role supporting migration and modernization of a production data platform on AWS, Snowflake, and Confluent/Kafka. The role involves infrastructure-as-code, operational support, incident response, and enabling governed data access. Candidates must be based in an eligible EMEA country and provide full US Central Time coverage.

Job description

Company Description

We are seeking a hands-on Senior Data Platform Engineer to support the modernization, migration, and reliability of a large-scale production data platform. This role combines data engineering with platform and DevOps operations across Snowflake, Confluent/Kafka, and AWS.

Enterprise experience strongly preferred.

Job Description

Key Responsibilities

  • Migrate data-platform infrastructure and workloads from legacy environments to modern AWS-based infrastructure.

  • Support connectivity, deployment, and operational prerequisites for workloads moving to AWS us-east-2.

  • Enable secure and governed access to data for platform consumers and downstream systems.

  • Modernize data-platform architecture, tooling, orchestration, storage, and operational practices.

  • Operate and migrate Snowflake, Confluent/Kafka, AWS, and related data-platform infrastructure across development, stage, and production environments.

  • Troubleshoot production issues and participate in incident response, testing, documentation, and runbook creation.

  • Deliver repeatable and auditable infrastructure changes using Terraform or comparable infrastructure-as-code practices, GitLab, monitoring, and documented change processes.

  • Coordinate migration work and technical dependencies across platform, data, and consuming teams.

Qualifications

Must-Have Skills

  • 3+ years of senior-level, hands-on production data-platform engineering experience with a platform or DevOps orientation and strong data experience.

  • Strong Python, Bash, and SQL skills.

  • Production experience with Snowflake, Confluent/Kafka, and AWS through one of two accepted depth profiles:

    • Deep Snowflake and AWS experience with working Kafka knowledge, including topics, connectors, and schemas; or

    • Deep Kafka/Confluent and AWS experience with working Snowflake knowledge.

  • Experience operating or migrating production systems across development, stage, and production environments.

  • Strong production troubleshooting, incident-response, testing, documentation, and cross-team communication skills.

  • Experience with least-privilege access, change control, secrets handling, and secure operational practices.

  • Hands-on experience using Terraform or infrastructure as code, GitLab, and monitoring to deliver repeatable and auditable changes.

Nice-to-Have Skills

  • Apache Spark and Hadoop, Hive, or HQL experience, including modernization or migration of legacy workloads.

  • Snowpark, alternatives to dbt, AWS Glue, Monte Carlo, or other data-quality and catalog tools.

  • Experience migrating legacy Airflow, Hadoop, or Hive workloads to cloud-native or managed platforms.

  • Experience aligning systems and operating practices during a company migration or acquisition.

  • Familiarity with Snowflake-to-Iceberg or Snowflake-to-data-lake migration patterns.

Required Tools & Platforms

  • Python, Bash, and SQL.

  • Snowflake.

  • Confluent and Apache Kafka, including topics, connectors, and schemas.

  • AWS, including production migration and operations.

  • Terraform or comparable infrastructure-as-code tooling.

  • GitLab.

  • Production monitoring and incident-response tooling.

Location, Time & Engagement

  • Candidates must be based in an eligible EMEA country approved for sourcing.

  • Full U.S. Central Standard Time coverage (UTC-6) is required.

  • Remote contract engagement for 45 hours per week.

  • This is not currently a contract-to-hire opportunity.

  • The successful candidate will use a client-provisioned AWS WorkSpace.

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