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 DescriptionKey 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.
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.
Skills Required
- 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
- Experience operating or migrating production systems across development, staging, 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 with Terraform or infrastructure as code, GitLab, and monitoring
- Enterprise experience
- Apache Spark and Hadoop, Hive, or HQL experience
- 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
- Based in an eligible EMEA country approved for sourcing
- Full U.S. Central Standard Time coverage, UTC-6
- Availability for a remote contract engagement of 45 hours per week
What We Do
Lifted, an Upwork Company, is a B2B SaaS platform that helps enterprise organizations source, contract, manage, and pay contingent talent globally and compliantly. It supports multiple engagement models, including independent contractors, staff augmentation, and employer-of-record, while integrating with MSPs and VMSs to provide centralized visibility, spend control, and audit-ready compliance, delivering a white-labeled talent experience for hiring managers and contingent workforce programs.
