Data Engineer (SQL, Python, ETL, Cloud)

$90,000 - $110,000/Yr

Ledgent - Los Angeles, CA

Full-time

Hybrid - Los Angeles, CA

Administrative and Support Services

About the position

We are seeking a highly skilled and motivated Data Engineer to join our dynamic data team. The ideal candidate will have deep expertise in SQL, cloud platforms, data modeling, and building production-ready ETL pipelines. This role will be essential in designing and maintaining scalable data infrastructure, ensuring seamless data integration, and optimizing end-to-end data workflows. As a key player in shaping our data architecture, you will contribute to building robust, cloud-based solutions that support data analytics and business intelligence initiatives across the organization.

Responsibilities

• Develop, test, and deploy ETL pipelines to move and transform data across multiple data sources.
• Build integrations with third-party tools, APIs, and services, ensuring data is synchronized and accessible.
• Manage and optimize data storage, particularly in cloud-based OLAP databases (e.g., Snowflake, Redshift).
• Work with cross-functional teams including data scientists, business analysts, and product teams to understand data needs and ensure effective solutions.
• Monitor and tune data processes and queries for optimal performance and efficiency.
• Help design, deploy, and maintain cloud infrastructure and storage.
• Maintain clear and comprehensive technical documentation of data pipelines, workflows, and infrastructure.
• Knowledge of containerization technologies like Docker and Kubernetes and experience with deploying data pipelines in containerized environments.

Requirements

• Bachelor's degree in Mathematics, Statistics, Economics, Computer Science, Engineering, or a related quantitative discipline.
• Strong skills with data manipulation/modeling and creating complex SQL query scripts.
• Hands-on experience with cloud-based data warehouses such as Snowflake or Redshift.
• Familiarity with ETL tools such as Fivetran, Stitch, Rivery, or Airbyte.
• Experience working with AWS cloud services including S3, AWS Batch, ECR, Lambda, SNS, SQS, and other managed cloud platforms.
• Experience writing production-ready, testable code in languages like Python, Scala, or Java.
• Familiarity with project management and documentation tools like JIRA Software, JIRA Service Management and Confluence.
• Experience with data transformation tools such as DBT (Data Build Tool).
• Advanced experience with API integrations and automating data ingestion.
• Experience with data orchestration tools like Apache Airflow or Luigi for scheduling and managing workflows.
• Experience with data modeling techniques such as Kimball, Inmon, or Data Vault.
• Experience with CI/CD pipelines, deployment, and automation using Git and other DevOps tools.
• Strong problem-solving skills and the ability to work independently and as part of a team.
• Excellent communication skills with the ability to explain complex technical concepts to non-technical stakeholders.

Nice-to-haves

• Understanding of data governance practices and tools for managing data quality, lineage, and security.
• Experience with large-scale data processing frameworks such as Spark or Hadoop.
• Knowledge of data streaming tools and best practices using Kafka, Kinesis, or similar technologies.
• Experience with NoSQL technologies like MongoDB, Cassandra, or Elasticsearch.