Job Summary :
We are seeking a highly skilled and experienced Senior Data Engineer to design, build, and maintain robust data pipelines and infrastructure that enable data-driven decision-making across the organization.
The ideal candidate will have deep expertise in data architecture, ETL processes, and cloud data platforms.
You will collaborate closely with data scientists, analysts, and software engineers to ensure high-quality, scalable, and reliable data Responsibilities :
- Design, develop, and maintain scalable and efficient data pipelines for batch and real-time processing.
- Build and optimize data architectures, data models, and storage solutions to support analytics and business intelligence needs.
- Collaborate with cross-functional teams including data scientists, analysts, and product managers to understand data requirements and deliver data solutions.
- Implement ETL / ELT processes to ingest data from various structured and unstructured sources.
- Ensure data quality, consistency, and reliability through robust validation and monitoring frameworks.
- Develop and maintain data warehouses, data lakes, and related infrastructure using cloud platforms (AWS, Azure, GCP).
- Optimize database performance and manage large-scale distributed data processing systems.
- Implement data security and governance best practices to ensure compliance with regulations.
- Mentor junior data engineers and contribute to the continuous improvement of engineering
standards and practices.
Stay updated with emerging data technologies and recommend innovative Skills Required :Proficiency in programming languages such as Python, Java, or Scala.Strong experience with big data technologies like Apache Spark, Hadoop, Kafka, or Flink.Expertise in SQL and working with relational databases (PostgreSQL, MySQL, SQL Server).Experience with cloud data platforms such as AWS (Redshift, S3, Glue), Azure (Synapse, Data Factory), or Google Cloud (BigQuery, Dataflow).Familiarity with data warehousing concepts and tools like Snowflake, Redshift, or GoogleBigQuery.
Hands-on experience with ETL / ELT tools and frameworks.Knowledge of containerization (Docker) and orchestration tools (Kubernetes) is a plus.Understanding of data governance, security, and compliance standards.Experience with version control (Git) and CI / CD pipelines for data engineering workflows(ref : hirist.tech)