Data Engineer

We are seeking a Data Engineer to build, optimize, and maintain scalable data platforms that power business intelligence, analytics, machine learning, and data-driven decision-making. The ideal candidate will have strong expertise in data engineering, ETL development, cloud platforms, and modern data architectures. You will work closely with data analysts, data scientists, product teams, and business stakeholders to deliver reliable and high-quality data solutions.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines for processing structured and unstructured data.
• Build and optimize ETL/ELT workflows to ensure efficient data ingestion, transformation, and delivery.
• Develop and manage data lakes, data warehouses, and modern data platforms.
• Ensure data quality, integrity, security, and governance across all data systems.
• Collaborate with business stakeholders to understand data requirements and translate them into technical solutions.
• Monitor, troubleshoot, and optimize data pipelines for performance and reliability.
• Implement automation and orchestration processes for data workflows.
• Support analytics, reporting, machine learning, and business intelligence initiatives.
• Document data models, workflows, and engineering processes.
• Stay current with emerging technologies and recommend improvements to the data ecosystem.Required Qualifications
• Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or a related field.
• 3+ years of experience in Data Engineering or related roles.
• Strong proficiency in SQL and database design principles.
• Experience with Python, Scala, Java, or other programming languages used for data processing.
• Hands-on experience building ETL/ELT pipelines and data integration solutions.
• Experience working with relational and NoSQL databases.
• Strong understanding of data modeling, data warehousing, and data architecture concepts.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud.
• Knowledge of big data technologies such as Spark, Hadoop, Databricks, or Kafka.
• Familiarity with workflow orchestration tools such as Airflow, Prefect, or similar platforms.
• Understanding of CI/CD practices and version control systems.Preferred Qualifications
• Experience with modern data warehouses such as Snowflake, Redshift, BigQuery, or Synapse.
• Knowledge of streaming and real-time data processing frameworks.
• Exposure to machine learning pipelines and MLOps concepts.
• Experience implementing data governance, data lineage, and security best practices.
• Familiarity with Infrastructure as Code (Terraform, CloudFormation, etc.).
• Experience working in SaaS, fintech, e-commerce, healthcare, or enterprise technology environments.