CareerPlanGet AI match score →
💼 Full-time🗓 2026-07-30

Core

Design, build, and maintain scalable data pipelines and ETL/ELT processes to enable data accessibility and reliability for analysts and scientists.

Role type

Data Engineer

Builds

Data pipelines, ETL/ELT workflows, and data storage/processing systems

Domain

Data Engineering / Big Data

Deliverable

production ML models | infrastructure

Required skills

Python, Java, Scala, SQL, PostgreSQL, MySQL, Oracle, Hadoop, Spark, Kafka, AWS, GCP, Azure, Redshift, BigQuery, Snowflake, ETL/ELT, data modeling, data warehousing

Preferred skills

Real-time data streaming, data governance, security, compliance, machine learning pipelines

Technologies

Python, Java, Scala, SQL, PostgreSQL, MySQL, Oracle, Hadoop, Spark, Kafka, AWS, GCP, Azure, Redshift, BigQuery, Snowflake

Responsibilities

Design and develop data pipelines and ETL/ELT processes; Collaborate with analysts and scientists to provide clean, structured data; Ensure performance and scalability of data systems; Integrate data from relational databases, NoSQL, APIs, and third-party platforms; Optimize data systems for speed and reliability; Implement data quality checks and monitoring; Maintain documentation for pipelines and architectures

Seniority

Mid-level, hands-on IC

Rewrite
## About the role We are seeking a skilled Data Engineer to design, build, and maintain scalable data pipelines that enable our organization to leverage data effectively. You will work closely with data analysts, data scientists, and other stakeholders to ensure data is accessible, reliable, and ready for analysis. ## Key Responsibilities - Design, develop, and maintain data pipelines, ETL/ELT processes, and workflows to handle large-scale datasets. - Collaborate with data analysts and data scientists to understand data requirements and provide clean, structured, and efficient data. - Ensure the performance, scalability, and reliability of data storage and processing systems. - Integrate data from multiple sources, including relational databases, NoSQL databases, APIs, and third-party platforms. - Optimize data systems for speed, reliability, and security. - Implement data quality checks, monitoring, and alerting mechanisms. - Maintain documentation for data pipelines, architectures, and processes. - Stay up-to-date with emerging data technologies and recommend improvements. ## Required Skills and Qualifications - Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or a related field. - Strong programming skills in languages such as Python, Java, or Scala. - Experience with SQL and database systems (e.g., PostgreSQL, MySQL, Oracle). - Experience with big data technologies (e.g., Hadoop, Spark, Kafka) is highly desirable. - Familiarity with cloud platforms (AWS, GCP, Azure) and cloud data tools (Redshift, BigQuery, Snowflake). - Knowledge of ETL/ELT processes and data modeling. - Understanding of data warehousing concepts and best practices. - Excellent problem-solving and communication skills. ## Preferred Qualifications - Experience with real-time data streaming and processing. - Familiarity with data governance, security, and compliance standards. - Experience in working with machine learning pipelines. ## What We Offer - Competitive salary and benefits - Opportunity to work with cutting-edge technologies - Collaborative and inclusive work environment - Career growth and professional development opportunities
Sourced via wellfound · Listed on CareerPlan, which tracks 70,000+ jobs from 20+ sources.
Apply on Wellfound ↗