Data Engineer

Data Engineer Location: Remote / Hybrid (USA) Duration: Long-Term Contract / Full-Time Work Authorization: US Citizen or Green Card Only Job Description We are seeking a skilled Data Engineer with 3–6 years of experience in designing, developing, and maintaining scalable data pipelines and data integration solutions. The ideal candidate will have strong expertise in SQL, Python, ETL processes, cloud data platforms, and modern big data technologies. You will work closely with data analysts, software engineers, and business stakeholders to build reliable and efficient data solutions. Required Skills • 3–6 years of experience as a Data Engineer • Strong SQL skills with experience in performance tuning and query optimization • Proficiency in Python for data processing and automation • Experience designing and developing ETL/ELT pipelines • Hands-on experience with Apache Spark and PySpark • Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform (GCP) • Experience with cloud data warehouses such as Snowflake, Amazon Redshift, Google BigQuery, or Azure Synapse • Experience with data orchestration tools such as Apache Airflow or Azure Data Factory • Strong knowledge of relational and NoSQL databases • Experience with data modeling and data warehousing concepts • Experience with Git and version control • Familiarity with Linux environments • Strong analytical and problem-solving skills • Experience working in Agile/Scrum environments Preferred Skills • Experience with Databricks • Experience with Kafka or other streaming technologies • Knowledge of Delta Lake and Lakehouse architecture • Experience with Docker and Kubernetes • Experience with Terraform or Infrastructure as Code • Experience with dbt (Data Build Tool) • Understanding of data governance, data quality, and data security • Cloud certifications (AWS, Azure, or GCP) Responsibilities • Design, develop, and maintain scalable ETL/ELT pipelines • Build and optimize data ingestion and transformation processes • Develop data models and support enterprise data warehouse solutions • Work with structured and unstructured data from multiple sources • Optimize database performance and improve query efficiency • Implement data validation, quality checks, and monitoring • Collaborate with cross-functional teams to understand business requirements • Support batch and real-time data processing solutions • Troubleshoot production issues and ensure high availability of data platforms • Create technical documentation and maintain data pipeline standards Education Bachelor's degree in Computer Science, Information Systems, Engineering, Mathematics, or a related field (or equivalent work experience).