We are seeking a detail-oriented, analytical, and technically skilled Data Engineer to join our team. In this role, you will be responsible for designing, developing, maintaining, and optimizing data pipelines and data infrastructure. You will work closely with data analysts, data scientists, software engineers, and business stakeholders to ensure reliable, scalable, and high-quality data is available for reporting, analytics, and business decision-making.
Key Responsibilities
- Design, develop, and maintain scalable data pipelines for collecting, processing, transforming, and integrating data from multiple sources.
- Develop and optimize ETL/ELT processes to efficiently move and transform data across systems.
- Extract, clean, transform, and load data from structured and unstructured sources.
- Develop and maintain data warehouses, data lakes, and data marts to support business intelligence and analytics.
- Write efficient SQL queries for data extraction, transformation, validation, and analysis.
- Work with relational and non-relational databases to store and manage large datasets.
- Perform data profiling, data cleansing, and data quality checks to ensure accuracy, consistency, and completeness.
- Monitor data pipelines and troubleshoot data processing issues, failures, and performance bottlenecks.
- Collaborate with Data Analysts, Data Scientists, Software Engineers, and business teams to understand data requirements.
- Develop data models and optimize database structures to support reporting and analytical requirements.
- Implement data validation and error-handling processes to maintain data integrity.
- Automate repetitive data-processing and data-integration tasks using appropriate programming and scripting tools.
- Optimize existing data pipelines, queries, and workflows for improved performance and scalability.
- Maintain technical documentation for data pipelines, data models, processes, and integrations.
- Support the development and maintenance of dashboards, reports, and analytical datasets.
- Ensure data security, access controls, governance, and compliance requirements are followed.
- Participate in code reviews, testing, deployment, and continuous improvement of data engineering solutions.
- Support data migration, system integration, and implementation of new data sources when required.
- Identify opportunities to improve data architecture, pipeline reliability, automation, and overall data operations.
Qualifications
- Bachelor's degree in Computer Science, Information Technology, Data Science, Engineering, Mathematics, Statistics, or a related field.
- 0–3 years of experience in Data Engineering, Data Analytics, Database Development, ETL, or a related role.
- Strong knowledge of SQL and relational database concepts.
- Proficiency in at least one programming language such as Python, Java, or Scala.
- Understanding of ETL/ELT concepts and data pipeline development.
- Familiarity with databases such as MySQL, PostgreSQL, SQL Server, Oracle, or similar technologies.
- Understanding of data warehousing concepts, dimensional modeling, and data transformation.
- Familiarity with data structures, algorithms, and database optimization techniques.
- Basic understanding of APIs, data integration, and file-based data processing.
- Familiarity with version control systems such as Git/GitHub.
- Strong analytical, problem-solving, and troubleshooting skills.
- Good understanding of data quality, validation, and data management principles.
- Strong communication skills and the ability to collaborate with technical and non-technical teams.
- Strong attention to detail and ability to manage multiple tasks and priorities.
Preferred Qualifications
- Experience with cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform (GCP).
- Familiarity with cloud data services such as Amazon S3, AWS Glue, Redshift, Azure Data Factory, Azure Synapse, Google BigQuery, or similar platforms.
- Knowledge of big data technologies such as Apache Spark, Databricks, Hadoop, or Kafka.
- Experience with orchestration tools such as Apache Airflow, Azure Data Factory, AWS Glue, or similar platforms.
- Familiarity with data visualization and business intelligence tools such as Power BI or Tableau.
- Knowledge of data lake, data warehouse, and modern data architecture concepts.
- Experience working with REST APIs, JSON, XML, CSV, and other data formats.
- Understanding of CI/CD, DevOps practices, and automated deployment processes.
- Familiarity with Docker, Kubernetes, or containerized data-processing environments.
- Understanding of data governance, metadata management, and data security practices.
- Experience with Agile/Scrum methodologies and working in cross-functional development teams.
- Knowledge of machine learning data pipelines and feature engineering is an added advantage.
- Relevant certifications in AWS, Azure, GCP, Databricks, Snowflake, or Data Engineering are an added advantage.
What We Offer
- Competitive salary and comprehensive benefits package.
- Opportunities for professional growth and career advancement.
- Collaborative and innovative work environment.
- Exposure to modern data engineering tools, cloud technologies, and data platforms.
- Hands-on experience working with large datasets and real-world data engineering projects.
- Opportunities to work with cross-functional teams including Data Analysts, Data Scientists, Software Engineers, and Business Stakeholders.
- Exposure to modern ETL/ELT, data warehousing, data pipeline, and cloud technologies.
- Opportunities to develop strong technical expertise in data engineering and cloud-based data platforms.
- Work on diverse projects involving data integration, automation, analytics, and business intelligence.
Pay: $119,000.00 - $145,000.00 per year
Benefits:
Work Location: Hybrid remote in California
