Data Engineer

About the JobSkillsdata lakehousepythonetl pipelinesData Engineeringapache hopDatabasesNoSQLSQLLocation: Bangalore (5 days work from office, HSR Layout)Job Type: Full TimeIndustry: AgritechOpenings: Multiple- junior, mid level etcPython- MandatoryOverviewThe Data Engineer/ Senior Data Engineer will design, develop, and maintain scalable data pipelines and infrastructure to support data-driven decision-making and advanced analytics. This role requires deep expertise in data engineering, strong problem-solving skills, and the ability to collaborate with cross-functional teams to deliver robust data solutions.Key Responsibilities● Data Pipeline Development: Design, build, and optimize scalable, secure, and reliable data pipelines to ingest, process, and transform large volumes of structured and unstructured data.● Data Architecture: Architect and maintain data storage solutions, including data lakes, data warehouses, and databases, ensuring performance, scalability, and cost-efficiency.● Data Integration: Integrate data from diverse sources, including APIs, third-party systems, and streaming platforms, ensuring data quality and consistency.● Performance Optimization: Monitor and optimize data systems for performance, scalability, and cost, implementing best practices for partitioning, indexing, and caching.● Collaboration: Work closely with data scientists, analysts, and software engineers to understand data needs and deliver solutions that enable advanced analytics, machine learning, and reporting.● Data Governance: Implement data governance policies, ensuring compliance with data security, privacy regulations (e.g., GDPR, CCPA), and internal standards.● Automation: Develop automated processes for data ingestion, transformation, and validation to improve efficiency and reduce manual intervention.● Mentorship: Guide and mentor junior data engineers, fostering a culture of technical excellence and continuous learning.● Troubleshooting: Diagnose and resolve complex data-related issues, ensuring high availability and reliability of data systems.Required Qualifications● Education: Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field.● Experience: 5+ years of experience in data engineering or a related role, with a proven track record of building scalable data pipelines and infrastructure.● Technical Skills:○ Proficiency in programming languages such as Python, Java, or Scala.○ Expertise in SQL and experience with NoSQL databases (e.g., MongoDB, Cassandra).○ Strong experience with cloud platforms (e.g., AWS, Azure, GCP) and their data services (e.g., Redshift, BigQuery, Snowflake).○ Hands-on experience with ETL/ELT tools (e.g., Apache Airflow, Talend, Informatica) and data integration frameworks.○ Familiarity with big data technologies (e.g., Hadoop, Spark, Kafka) and distributed systems.○ Knowledge of containerization and orchestration tools (e.g., Docker, Kubernetes) is a plus.● Soft Skills:○ Excellent problem-solving and analytical skills.○ Strong communication and collaboration abilities.○ Ability to work in a fast-paced, dynamic environment and manage multiple priorities.● Certifications (optional but preferred): Cloud certifications (e.g., AWS Certified Data Analytics, Google Professional Data Engineer) or relevant data engineering certifications.Preferred Qualifications● Experience with real-time data processing and streaming architectures.● Familiarity with machine learning pipelines and MLOps practices.● Knowledge of data visualization tools (e.g., Tableau, Power BI) and their integration with data pipelines.● Experience in industries with high data complexity, such as finance, healthcare, or e-commerce.Work Environment● Team: Collaborative, cross-functional team environment with data scientists, analysts, and business stakeholders.● Hours: Full-time, with occasional on-call responsibilities for critical data systems