Senior Data Engineer
Skills
About the role
Job Title: Senior Data Engineer
Experience: 6+ Years Employment Type: Full-Time
About the Role
We are seeking an experienced Senior Data Engineer with 6+ years of expertise in designing, building, and maintaining enterprise-scale data platforms. The ideal candidate should have strong experience in ETL/ELT development, data integration, cloud-based data engineering, and advanced analytics support. You will work closely with business stakeholders, analytics teams, and data scientists to deliver reliable, scalable, and high-performance data solutions.
Key Responsibilities
Design, develop, and maintain scalable ETL/ELT pipelines for enterprise data processing and analytics.
Develop data ingestion, transformation, and integration workflows across multiple data sources.
Build and optimize data pipelines to support reporting, business intelligence, and advanced analytics.
Collaborate with business users, analysts, and data scientists to understand data requirements and deliver effective solutions.
Ensure high data quality, consistency, reliability, and integrity across data platforms.
Optimize pipeline performance, scalability, and resource utilization.
Support production and non-production data environments, ensuring high availability and operational stability.
Participate in data model design, enhancement, and optimization.
Develop and maintain reusable data engineering frameworks and automation processes.
Troubleshoot data pipeline failures and resolve performance bottlenecks.
Perform data validation, reconciliation, and quality checks.
Support exploratory and investigative analytics by preparing clean and reliable datasets.
Work with modern data engineering and analytics tools to accelerate data processing and reporting.
Collaborate with cross-functional teams throughout the software development lifecycle.
Document data architecture, pipelines, workflows, and technical processes.
Mentor junior engineers and promote data engineering best practices.
Required Skills
Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
6+ years of experience in Data Engineering and ETL/ELT development.
Strong expertise in SQL and database optimization.
Experience designing and developing scalable ETL/ELT pipelines.
Strong knowledge of data warehousing concepts and dimensional data modeling.
Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.
Hands-on experience with modern data engineering tools and frameworks.
Experience with Apache Spark, Databricks, or similar big data technologies.
Proficiency in Python for data engineering and automation.
Experience working with relational and NoSQL databases.
Knowledge of workflow orchestration tools such as Apache Airflow or similar.
Experience integrating structured, semi-structured, and unstructured data sources.
Strong understanding of data governance, security, and compliance best practices.
Experience with Git and version control systems.
Excellent analytical, troubleshooting, and problem-solving skills.
Strong communication and collaboration skills.
Preferred Qualifications
Experience with enterprise-scale analytics platforms.
Knowledge of data lakes and lakehouse architectures.
Familiarity with AI/ML data pipelines and analytics use cases.
Experience with containerization technologies such as Docker and Kubernetes.
Exposure to CI/CD practices for data engineering workflows.
Experience working in Agile/Scrum environments.
Work Location: Remote
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