Job Specifications
Contract to hire Data Engineer opportunity for large entertainment and media corporations. This will be hybrid 3 days a week onsite in Burbank, CA (local candidates only).
***** NO C2C ******
Must have experience with development of batch and streaming pipelines using AWS-native tools (Glue, Lambda, Step Functions, Kinesis) and modern orchestration frameworks.
The Senior Data Engineer plays a hands-on role within the Platform Pod, ensuring data pipelines, integrations, and services are performant, reliable, and reusable. This role partners closely with Data Architects, Cloud Architects, and application pods to deliver governed, AI/ML-ready data products.
Job Responsibilities / Typical Day in the Role
Design & Build Scalable Data Pipelines
Lead development of batch and streaming pipelines using AWS-native tools (Glue, Lambda, Step Functions, Kinesis) and modern orchestration frameworks.
Implement best practices for monitoring, resilience, and cost optimization in high-scale pipelines.
Collaborate with architects to translate canonical and semantic data models into physical implementations.
Enable Analytics & AI/ML Workflows
Build pipelines that deliver clean, well-structured data to analysts, BI tools, and ML pipelines.
Work with data scientists to enable feature engineering and deployment of ML models into production environments.
Ensure Data Quality & Governance
Embed validation, lineage, and anomaly detection into pipelines.
Contribute to the enterprise data catalog and enforce schema alignment across pods.
Partner with governance teams to implement role-based access, tagging, and metadata standards.
Mentor & Collaborate Across Pods
Guide junior data engineers, sharing best practices in pipeline design and coding standards.
Participate in pod ceremonies (backlog refinement, sprint reviews) and program-level architecture syncs.
Promote reusable services and reduce fragmentation by advocating platform-first approaches.
Years experience:
3-7+ years of experience in data engineering, with hands-on expertise in AWS services (Glue, Kinesis, Lambda, RDS, DynamoDB, S3) and orchestration tools (Airflow, Step Functions).
Must Have Skills / Requirements
Data Engineering Experience with hands-on expertise in AWS services (Glue, Kinesis, Lambda, RDS, DynamoDB, S3) and orchestration tools (Airflow, Step Functions).
Proven ability to optimize pipelines for both batch and streaming use cases.
Knowledge of data governance practices, including lineage, validation, and cataloging.
Technology Requirements:
Experience with data engineering, with hands-on expertise in AWS services (Glue, Kinesis, Lambda, RDS, DynamoDB, S3) and orchestration tools (Airflow, Step Functions).
Strong skills in SQL, Python, PySpark, and scripting for data transformations.
Experience working with modern data platforms (Snowflake, Databricks, Redshift, Informatica).
Proven ability to optimize pipelines for both batch and streaming use cases.
Knowledge of data governance practices, including lineage, validation, and cataloging.
Nice to Have Skills / Preferred Requirements
Proven ability to optimize pipelines for both batch and streaming use cases.
Knowledge of data governance practices, including lineage, validation, and cataloging.
Strong collaboration and mentoring skills; ability to influence pods and domains.
About the Company
Founded in 2001, Odesus is an Information Technology Consulting and Staffing Firm. Over the course of the past 20 years, Odesus has established itself as one of the premiere firms providing services to banking, financial, entertainment and insurance clients, among other industries. Our business model is designed to provide services to a few premiere clients in a joint partnership to enhance performance and delivery. Today, Odesus' model has evolved so that we are a complete solutions provider focused on the deployment of IT ...
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