Note: The job is a remote job and is open to candidates in USA. CyOpsPath is a job discovery platform. The Data Engineer will design, build, and maintain scalable data pipelines, warehouses, streaming frameworks, and data lakes. The role also focuses on data modeling, quality assurance, performance optimization, and collaboration with technical and business stakeholders.
Responsibilities
- Data Pipeline Engineering: Design, construct, and maintain scalable, high-performance ETL/ELT pipelines to ingest, transform, and load data from diverse sources
- Architecture & Infrastructure: Build and optimize data warehousing solutions, streaming frameworks, and data lakes to ensure high availability and scalability
- Data Modeling: Develop optimized relational and non-relational data models suited for reporting, analytics, and machine learning applications
- Quality & Reliability: Implement automated testing, monitoring, and validation checks to guarantee data accuracy, consistency, and integrity
- Performance Tuning: Monitor system performance, troubleshoot bottlenecks, and optimize query efficiency across large-scale datasets
- Cross-Functional Collaboration: Partner with data scientists, software engineers, and business stakeholders to understand requirements and deliver reliable data solutions
Skills
- 3+ years of experience in Data Engineering, Software Development, or a related technical role
- Proficiency in Python, SQL, or Scala/Java for data manipulation and pipeline development
- Strong experience with modern data tools and warehouses (e.g., Snowflake, BigQuery, Redshift, Databricks, Apache Airflow, dbt)
- Hands-on experience with streaming/distributed computing platforms like Apache Kafka or Apache Spark
- Deep knowledge of both relational (PostgreSQL, MySQL) and NoSQL databases
- Experience building and deploying data infrastructure on AWS, GCP, or Azure
- Familiarity with Git, containerization (Docker, Kubernetes), and CI/CD workflows
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