Data Engineer

We are seeking an experienced Data Engineer II to design, develop, and maintain scalable data pipelines and centralized data solutions that support analytics, reporting, dashboards, and operational decision-making. The ideal candidate will have strong expertise in SQL, Python/Java, ETL, data modeling, PostgreSQL, MongoDB, and Big Data technologies , along with experience working across cloud, containerization, and modern data platforms.

Key Responsibilities

• Design, develop, and maintain scalable data ingestion, ETL, and transformation pipelines .
• Integrate data from multiple databases, APIs, applications, files, and operational systems.
• Develop and maintain data models, schemas, tables, views, and reusable data structures .
• Build and optimize data solutions using PostgreSQL, SQL Server, MongoDB , and other relational/NoSQL platforms.
• Transform raw and semi-structured data into high-quality, analytics-ready datasets.
• Implement data validation, quality, accuracy, consistency, and reliability controls .
• Develop automated data pipelines and troubleshoot data integration issues.
• Apply performance tuning, indexing, query optimization, and database best practices .
• Support dashboards, reporting, and visualization platforms such as Grafana, Tableau, and Power BI .
• Work with Big Data technologies and large-scale operational and analytical datasets.
• Collaborate with architects, product owners, developers, analysts, and business stakeholders to define data requirements and technical solutions.
• Integrate data through REST APIs, file-based ingestion, and system interfaces .
• Participate in code reviews, testing, deployments, production support, and root-cause analysis.
• Document data flows, transformations, schemas, pipelines, and technical solutions.
• Contribute to Agile planning, estimation, sprint activities, and continuous improvement .
• Follow CI/CD, containerization, and modern DevOps practices for data engineering solutions.

Required Qualifications

• 3+ years of experience in Data Engineering, ETL, Data Integration, or a related role.
• Strong SQL skills with experience designing and optimizing relational database solutions.
• Hands-on experience with PostgreSQL, SQL Server , or similar databases.
• Experience with MongoDB or other NoSQL technologies .
• Proficiency in at least one data-processing language such as Python, Java, or Scala .
• Experience developing and maintaining automated ETL/data pipelines .
• Strong understanding of data modeling, schema design, data warehousing, and data integration concepts .
• Experience with data quality, validation, and reconciliation processes.
• Experience working with REST APIs, file ingestion, and system integrations .
• Knowledge of database performance tuning, indexing, and query optimization .
• Experience working with large-scale operational or analytical datasets.
• Familiarity with Big Data technologies .
• Experience with Agile development methodologies and CI/CD practices .
• Strong analytical, troubleshooting, communication, and documentation skills.

Preferred / Additional Qualifications

• Experience with Cloudera environments.
• Cloudera Administration or Data Engineering certification is a plus.
• Experience with Cloud technologies such as AWS, Azure, or GCP.
• Knowledge of Docker/containerization technologies.
• Experience with OpenShift/Kubernetes environments.
• Cloud, Docker/Container, or OpenShift certifications are highly desirable.
• Experience with Spark, Hadoop, Kafka, Hive, or other Big Data technologies .
• Experience supporting Grafana, Tableau, Power BI , or similar analytics platforms.