Data Engineer - Python/SQL/ETL

<p><p><b>Key Responsibilities : </b><br/><br/></p><p>- Design, develop, test, and maintain robust data architectures, pipelines, and ETL processes.<br/><br/></p><p>- Ensure data quality, integrity, and security across systems and workflows.<br/><br/></p><p>- Optimize data systems for performance, scalability, and cost-efficiency.<br/><br/></p><p>- Collaborate with cross-functional teams to gather requirements and enable data-driven analytics and insights.<br/><br/></p><p>- Monitor, troubleshoot, and resolve issues within data workflows and systems.<br/><br/></p><p>- Maintain documentation for data processes, standards, and best Skills & Qualifications : </b></p><p><br/></p>- Bachelors/Masters degree in Computer Science, Information Technology, Data Engineering, or related field.<br/><br/></p><p>- Proven experience with data pipeline tools and ETL frameworks (e.g., Apache Airflow, Talend, NiFi).<br/><br/></p><p>- Strong proficiency in SQL and experience with relational/non-relational databases (e.g., MySQL, PostgreSQL, MongoDB).<br/><br/></p><p>- Hands-on experience with big data tools (e.g., Hadoop, Spark, Kafka).<br/><br/></p><p>- Proficiency in Python/Java/Scala for data processing.<br/><br/></p><p>- Knowledge of cloud platforms (AWS, Azure, GCP) and their data services.<br/><br/></p><p>- Familiarity with data warehousing solutions (e.g., Snowflake, Redshift, BigQuery).<br/><br/></p><p>- Strong problem-solving, troubleshooting, and communication Skills (Good to Have) : </b></p><p><br/></p>- Experience with containerization/orchestration (Docker, Kubernetes).<br/><br/></p><p>- Knowledge of machine learning pipelines and integration.<br/><br/></p><p>- Exposure to data governance and compliance practices.</p><br/></p> (ref:hirist.tech)