# Sr. Data Engineer

**Company:** [Storable](https://hotfix.jobs/companies/storable)
**Location:** Remote
**Role:** Data Engineering
**Experience:** 5+ years
**Skills:** Apache Airflow, Spark, Apache Iceberg, Trino, Presto, Aws S3, Aws Redshift, Aws Glue, Aws Athena, AWS Lambda, Python, ETL, ELT, Data Warehousing, Data Modeling
**Posted:** 2026-04-16

> Builds and maintains scalable data pipelines, ETL/ELT processes, and workflows using Airflow, Spark, Trino, and AWS services to support analytics and product innovation. Requires 5+ years experience in data engineering with Python proficiency.

## Job Description

## Key Responsibilities

- **Build & Maintain Data Pipelines**: Design, implement, and maintain scalable data pipelines using modern data tools to process and manage large datasets efficiently.
- **ETL Development**: Develop and optimize ETL/ELT pipelines to ingest, transform, and deliver data from multiple internal and external sources.
- **Workflow Orchestration**: Build and manage workflows using **Apache Airflow** to ensure reliable scheduling and monitoring of data processes.
- **Query Engines & Processing Frameworks**: Leverage tools such as **Trino (Presto)**, **Apache Spark**, and related distributed processing technologies to support analytics and data applications.
- **Data Modeling & Warehousing**: Contribute to schema design and data modeling efforts to ensure clean, well-structured, and scalable data architecture.
- **Data Quality & Governance Support**: Implement monitoring, validation checks, and best practices to ensure data accuracy, consistency, and reliability.
- **Optimize Data Infrastructure**: Utilize **AWS** services (**S3**, **Redshift**, **Glue**, **Athena**, **Lambda**) and modern data technologies (e.g., **Apache Iceberg**) to support a scalable and efficient data platform.
- **Cross-Functional Collaboration**: Partner with engineering, product, analytics, and business teams to understand requirements and deliver high-quality data solutions.
- **Monitor & Improve Performance**: Proactively monitor pipelines and workflows, troubleshoot issues, and continuously improve performance and reliability.

## Qualifications

- 5+ years of experience building and maintaining data pipelines or working in data engineering or related roles.
- Hands-on experience with data tools such as **Apache Airflow**, **Apache Spark**, **Apache Iceberg**, **Trino/Presto**, and **AWS** services (**S3**, **Redshift**, **Glue**, **Athena**, **Lambda**).
- Proficiency in **Python** (or similar language) for data processing and pipeline development.
- Solid understanding of data warehousing concepts, schema design, and data modeling best practices.
- Experience deploying and supporting data pipelines in production environments.
- Strong analytical skills and ability to diagnose and resolve data-related issues.
- Ability to communicate effectively with both technical and non-technical stakeholders and work in cross-functional teams.

## Bonus Points

- Experience with visualization tools such as **Looker** or **Tableau**.
- Exposure to data governance, privacy, and quality frameworks.
- Familiarity with **CI/CD** practices and version control for data workflows.

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