<p><strong>Overview</strong></p><p> The Data Engineer is responsible for building and maintaining the data infrastructure that powers analytics, reporting, and data-driven decision-making across the organization. This role requires hands-on experience with data modeling, ETL/ELT development, and modern cloud data platforms. The ideal candidate is skilled at transforming raw data into clean, reliable datasets and optimizing data pipelines for performance and scalability.</p><p><strong>Key Responsibilities</strong></p><ul><li>Design, build, and maintain <strong>data pipelines</strong> and <strong>ETL/ELT workflows</strong> that move and transform data from various sources into centralized data warehouses or data lakes.</li><li>Develop and manage <strong>data models</strong>, schemas, and metadata to ensure consistency, scalability, and performance.</li><li>Work with large, complex datasets using tools like <strong>SQL, Python, and Spark</strong> to automate data ingestion and transformation.</li><li>Collaborate with analysts, data scientists, and business stakeholders to understand data needs and support analytical initiatives.</li><li>Implement and maintain <strong>data quality, governance, and validation processes</strong> to ensure accuracy and reliability.</li><li>Optimize data pipeline performance and cost across cloud environments such as <strong>AWS, Azure, or Google Cloud</strong>.</li><li>Support <strong>data warehouse development</strong> using platforms such as <strong>Snowflake, Redshift, BigQuery, or Synapse</strong>.</li><li>Troubleshoot and resolve data issues in production environments, ensuring minimal downtime and data integrity.</li><li>Maintain documentation for data pipelines, system architecture, and transformation logic.</li><li>Stay current with emerging data engineering technologies and recommend improvements to architecture and process design.</li></ul><p><br></p>

<p><strong>Qualifications</strong></p><ul><li>Bachelor’s degree in Computer Science, Information Systems, Data Engineering, or a related field.</li><li>3–5 years of experience in data engineering or a related technical role.</li><li>Strong proficiency in <strong>SQL</strong> and experience with <strong>Python or Scala</strong> for data processing.</li><li>Experience building data pipelines using <strong>ETL/ELT frameworks</strong> (Airflow, dbt, AWS Glue, Azure Data Factory, or Talend).</li><li>Familiarity with <strong>data warehousing concepts</strong> and dimensional modeling.</li><li>Hands-on experience with at least one <strong>cloud data platform</strong> (AWS, Azure, or GCP).</li><li>Understanding of version control systems (Git) and CI/CD pipelines for data deployments.</li><li>Strong problem-solving skills and ability to work independently within cross-functional teams.</li></ul><p><strong>Preferred</strong></p><ul><li>Experience with <strong>Spark, Databricks, or Kafka</strong> for streaming and big data processing.</li><li>Familiarity with <strong>infrastructure-as-code tools</strong> (Terraform, CloudFormation).</li><li>Experience with <strong>containerization technologies</strong> such as Docker or Kubernetes.</li><li>Exposure to <strong>data security, compliance, and privacy standards</strong> (GDPR, SOC 2, etc.).</li></ul><p><br></p>

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