Note: The job is a remote job and is open to candidates in USA. LHH is seeking a Senior Data Engineer to build and optimize modern, scalable cloud-based data platforms. The role focuses on data pipelines, Lakehouse and data warehouse architecture, workflow orchestration, data quality and governance, and enabling enterprise analytics through collaboration with data and engineering teams.
Responsibilities
- Design and implement scalable Lakehouse and data warehouse solutions in AWS
- Build and maintain robust data pipelines for ingesting, transforming, and curating large datasets
- Develop and optimize data models, schemas, and storage strategies
- Support data cataloging, metadata management, and governance initiatives
- Develop ETL/ELT pipelines using Python, PySpark, AWS Glue, and related technologies
- Create batch and streaming data processing solutions
- Build transformation workflows using dbt
- Optimize performance across large-scale data processing and analytics environments
- Design and support workflow orchestration using Apache Airflow
- Monitor pipeline health and implement automated alerting and recovery processes
- Develop CI/CD processes for data engineering workflows
- Promote automation and infrastructure-as-code best practices
- Ensure data accuracy, consistency, reliability, and security
- Implement monitoring, validation, and lineage solutions
- Maintain technical documentation and support governance frameworks
- Partner with data consumers, analysts, and engineering teams to deliver scalable solutions
- Enable self-service analytics through well-designed datasets and semantic models
- Contribute to architectural decisions and engineering best practices
Skills
- 7+ years of data warehousing and OLAP experience
- 7+ years of data modeling, database architecture, and schema design experience
- 5+ years of SQL experience
- 3+ years of Python development experience
- Experience with AWS-based data platforms and services
- Hands-on experience with:
- AWS S3
- Redshift
- AWS Glue
- Apache Airflow
- PySpark
- Dbt
- Experience building ETL/ELT pipelines and integrating data from APIs
- Strong understanding of dimensional modeling and data warehouse design
- Experience implementing CI/CD pipelines for data workflows
- Experience with data cataloging and metadata management
- Excellent communication and collaboration skills
- Experience with real-time or streaming data architectures
- Exposure to business intelligence platforms such as Tableau, Amazon QuickSight, or Looker
- Experience supporting large-scale cloud analytics environments
- Knowledge of modern DataOps and infrastructure automation practices
Benefits
- Fully remote opportunity
- Annual bonus potential
- Medical insurance
- Dental insurance
- Vision insurance
- Life insurance
- Short-term disability
- Additional voluntary benefits
- EAP program
- Commuter benefits
- 401K plan
- Available paid leave may include Paid Sick Leave, where required by law
- Any other paid leave required by Federal, State, or local law
- Holiday pay upon meeting eligibility criteria
Company Overview
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