Sr. Data Engineer
Company Profile
Logicbroker provides modern dropship and marketplace solutions that connect retailers and brands to Connect, Orchestrate, and Grow their commerce platform to take control of their customer experience. Through curated expanded assortment, flexible integration tools, and automated onboarding procedures, Logicbroker clients enjoy unmatched speed-to-market capabilities. We work with mid-market and Enterprise manufacturers and retailers across a number of verticals including Health & Wellness, Home Improvement, Consumer Electronics, Toys & Babies, and Consumer Packaged Goods and service brands such as Samsung, Victoria’s Secret, Ace Hardware and more.
Position – Sr. Data Engineer
As a Senior Data Engineer at Logicbroker, you’ll help build and scale the data platform that powers insights, exception monitoring, and customer analytics across our order network. You’ll develop robust data pipelines, ensure high-quality data availability, and support machine learning and reporting initiatives with modern cloud-based tools.
Primary Duties and Responsibilities:
- Design and maintain batch and streaming ETL/ELT pipelines for commerce data.
- Ingest and process structured and semi-structured data (e.g., EDI, JSON, CSV, XML).
- Develop data models and schemas that support analytics and operational use cases.
- Collaborate with data consumers to build domain-specific data products.
- Ensure data integrity through validation, error handling, and automated testing.
- Optimize data storage in warehouses, lakes, and lakehouses (e.g., Databricks, Redshift, Snowflake).
- Build observability into data pipelines using logs, metrics, and alerting tools.
- Deploy and maintain workflow orchestration tools (Airflow, Dagster, etc.).
- Automate data lineage, cataloging, and governance tracking.
- Participate in technical design reviews and influence data architecture decisions.
- Write and maintain documentation on pipeline logic, transformations, and data models.
- Contribute to infrastructure automation and DevOps for data pipelines.
- Collaborate with software engineers to integrate data services with core platform features.
- Identify and implement opportunities to reduce data latency and improve freshness.
- Support initiatives to leverage AI/ML, anomaly detection, and predictive analytics
Essential Skills, Experience & Education
- 5–8+ years of experience in data engineering, backend engineering, or analytics engineering.
- Strong Python and SQL development skills for data processing and transformation.
- Experience with distributed data processing tools like Spark, Flink, or Kafka.
- Familiarity with modern data warehouses (Databricks, Snowflake, Redshift, BigQuery).
- Proficiency with cloud data services and storage (e.g., AWS Glue, S3, Athena).
- Strong understanding of data modeling and schema design for analytics.
- Knowledge of orchestration tools (Airflow, Prefect, Dagster) and transformation tools (dbt).
- Hands-on experience with CI/CD practices and infrastructure-as-code.
- Familiarity with data governance, lineage, and privacy best practices.
- Ability to work with both technical and non-technical stakeholders.
- Solid debugging and performance optimization skills for data pipelines.
- Understanding of batch vs. stream processing tradeoffs and architecture.
- Comfortable working in Agile/Scrum environments and using Git-based workflows.
- Strong documentation, diagramming, and communication abilities.
- Bonus: Experience with EDI data formats, commerce transaction models, or reconciliation pipelines.
Compensation and Environment
Logicbroker offers a comprehensive retirement plan, workspace compensation, and more! Logicbroker embraces a truly remote work model. All Logicbroker employees will receive thorough training to kick-start their career with the organization, and help provide the tools needed to build a successful home workspace.
Logicbroker is an equal opportunity employer.