Why This Role Stands Out
You'll have the opportunity to build and optimize scalable data infrastructure in this remote Data Engineer role, contributing significantly to Helic & Co's analytics capabilities. If you're a mid-senior level professional with strong SQL, Python, and cloud platform experience, eager to drive data solutions and grow your career, this is a fantastic opportunity to explore. Apply today to join a forward-thinking technology company!
Quick Overview
Job Description
This is a remote position.
We are seeking a skilled and detail-oriented Data Engineer to design, build, and maintain scalable data infrastructure and pipelines. In this role, you will be responsible for ensuring reliable data flow, optimizing data systems, and enabling analytics and business intelligence across the organization.
Key Responsibilities
- Design, develop, and maintain scalable data pipelines (ETL/ELT processes)
- Build and optimize data architectures, including data warehouses and data lakes
- Develop and maintain robust data models to support analytics and reporting
- Write efficient SQL queries and manage large datasets
- Ensure data quality, integrity, and security across systems
- Monitor and troubleshoot data pipeline performance issues
- Collaborate with data analysts, data scientists, and software engineers
- Implement data governance and best practices
- Support real-time and batch data processing solutions
Qualifications
- Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related field
- Strong proficiency in SQL and database technologies
- Experience with programming languages such as Python, Java, or Scala
- Hands-on experience with data pipeline tools (e.g., Apache Airflow, Kafka)
- Familiarity with cloud platforms (AWS, Azure, Google Cloud)
- Understanding of data warehousing solutions (e.g., Snowflake, Redshift, BigQuery)
- Strong problem-solving and analytical skills
Preferred Skills
- Experience with big data technologies (e.g., Hadoop, Spark)
- Knowledge of data modeling techniques and schema design
- Familiarity with containerization tools (Docker, Kubernetes)
- Experience with CI/CD pipelines and DevOps practices
- Understanding of data security and compliance standards
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