We are seeking a hands-on Data Engineer to support a large-scale data platform modernization initiative. You will migrate approximately 1,000 datasets to Snowflake, adapt existing pipelines, and help deliver reliable orchestration with Apache Airflow 3. The architecture and technical approach are already defined, with the role focused on implementation and migration delivery through March 2027.
Enterprise experience strongly preferred.
Key Responsibilities
- Migrate pipelines from Apache Airflow 2 to Apache Airflow 3.
- Migrate Confluent connections between cloud regions.
- Migrate pipelines from Hive to Iceberg using Snowpark Connect.
- Adapt existing data pipelines to Snowflake while maintaining data quality and reliability.
- Support workflow scheduling and monitoring in Apache Airflow.
- Partner with the team to execute time-sensitive data migrations.
QualificationsMust-Have Skills
- 2+ years of experience.
- Strong software engineering fundamentals.
- Hands-on Python development experience.
- Advanced SQL, including complex joins, CTEs, window functions, and performance tuning.
- Snowflake data modeling.
- Apache Airflow experience developing and testing pipelines in Airflow and Python.
- Apache Kafka experience.
- Apache Spark experience, including hands-on PySpark.
- Experience with Iceberg and Parquet data formats.
- AWS experience, particularly S3 data lakes, partitioning, and lifecycle policies.
- Testing strategy experience and the ability to debug and test code hands-on.
- At least 2 years of industry experience working with large-scale datasets, including Airflow and Spark.
- Strong communication skills.
- Ability to work independently.
Nice-to-Have Skills
- Hands-on Snowflake migration experience, including data warehouse modernization and performance and cost optimization.
- Apache Airflow migration experience, including version upgrades, executor changes, or platform migrations.
- Experience using AI tools for development.
Additional InformationRequired Tools & Platforms
- Python and SQL.
- Snowflake, Apache Airflow, Apache Kafka, and Apache Spark/PySpark.
- Iceberg and Parquet.
- AWS S3.
- The migration environment also includes Confluent, Hive, and Snowpark Connect.
Location, Time & Engagement
- Open to candidates in eligible EMEA and APAC locations.
- Coverage until 12:00 PM Pacific Time is required.
- Remote contract engagement for 40 hours per week.
- Expected engagement through March 31, 2027; start date to be confirmed.
- Two openings are available.
- This is not currently a contract-to-hire opportunity.
Skills Required
- At least 2 years of industry experience, including work with large-scale datasets, Airflow, and Spark
- Strong software engineering fundamentals
- Hands-on Python development experience
- Advanced SQL, including complex joins, CTEs, window functions, and performance tuning
- Snowflake data modeling experience
- Apache Airflow experience developing and testing pipelines with Airflow and Python
- Apache Kafka experience
- Apache Spark experience, including hands-on PySpark
- Experience with Iceberg and Parquet data formats
- AWS experience, particularly S3 data lakes, partitioning, and lifecycle policies
- Testing strategy experience and ability to debug and test code hands-on
- Strong communication skills
- Ability to work independently
- Hands-on Snowflake migration experience, including data warehouse modernization and performance and cost optimization
- Apache Airflow migration experience, including version upgrades, executor changes, or platform migrations
- Experience using AI tools for development
- Enterprise experience
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.
