Senior Data Engineer

Core Responsibilities: Design, build, and maintain robust ETL/ELT pipelines.Develop and optimize data ingestion, transformation, and processing workflows.Ensure data reliability, performance, and scalability.Implement data quality, validation, and monitoring within pipelines.Support analytics, BI, and AI/ML use cases with trusted datasets.Technical Skills:Strong expertise in SQL and performance tuning.Proficiency in Python, Spark, or Scala.Hands-on experience with Data Warehouses, Data Lakes, Lakehouse architectures.Hand-on experience with Cloud platforms (AWS, Azure, or GCP).Experience with orchestration tools (Airflow, Azure Data Factory, Dagster).Experience with streaming / real-time data (Kafka, event-driven pipelines).Familiarity with CI/CD, Git, and DevOps practices.Data Architecture & Integration:Ability to work closely with Data Architects to implement target architectures.Experience integrating data from APIs, databases, files, and SaaS platforms.Understanding of data modeling and analytics-ready schemas.Data Governance & Security:Awareness of data governance, data quality, and metadata practices.Experience implementing data access controls and security.Understanding of privacy and compliance requirements.Leadership & Collaboration:Acts as a technical lead on data engineering initiatives.Mentors junior data engineers and reviews code.Strong collaboration with product, analytics, and business teams.Experience:5+ years of experience in data engineering, data platforms, or analytics engineering.Proven experience building and operating scalable, production-grade data pipelines.Experience working in complex, multi-source enterprise environments.Education & Certifications:Bachelor’s degree in computer science, Engineering, or related field.Cloud or data engineering certifications are a plus.