Data Engineer

Job Title: Data Engineer Job Summary: We are seeking a skilled and motivated Data Engineer to join our growing data team. In this role, you will be responsible for building and maintaining scalable data pipelines, optimizing data workflows, and supporting analytics and business intelligence initiatives. You will work closely with data scientists, analysts, and software engineers to ensure data availability, quality, and security across the organization. Key Responsibilities: Design, develop, and maintain robust and scalable data pipelines (ETL/ELT) using modern data engineering tools and frameworks. Build and optimize data architecture and data models to support analytics and reporting needs. Integrate data from various sources (APIs, databases, cloud storage, etc.) into a centralized data platform. Implement data quality checks and ensure data integrity across all pipelines. Collaborate with stakeholders to understand data requirements and deliver timely, high-quality data solutions. Monitor data pipeline performance and troubleshoot data-related issues. Ensure compliance with data governance and data security policies. Automate manual processes and improve data workflows for efficiency and scalability. Support deployment and operation of data infrastructure in cloud environments (e.g., AWS, Azure, GCP). Required Qualifications: Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field. 2+ years of experience as a Data Engineer or in a similar role. Strong proficiency in SQL and experience working with relational databases (e.g., PostgreSQL, MySQL). Experience with data pipeline orchestration tools (e.g., Apache Airflow, Prefect, dbt). Proficiency in at least one programming language (e.g., Python, Java, Scala). Familiarity with cloud platforms (e.g., AWS, GCP, Azure) and services like S3, Redshift, BigQuery, or Snowflake. Understanding of data warehousing concepts and dimensional modeling. Experience with version control systems like Git. Preferred Qualifications: Experience with real-time data processing frameworks (e.g., Kafka, Spark, Flink). Knowledge of CI/CD and DevOps practices in a data engineering context. Familiarity with data governance tools and practices (e.g., data catalogs, lineage tracking). Experience with containerization and orchestration tools (e.g., Docker, Kubernetes). What We Offer: Competitive salary and benefits package. Flexible work hours and remote work options. Opportunity to work with a talented and passionate team on cutting-edge data projects. Professional development opportunities and career growth support.