Data Engineer

Job Description

Job Title: Data Engineer (Mid-Level) Experience: 3 to 5 Years Location: Bangalore Department: Data Engineering / Analytics / IT Summary: entomo is an Equal Opportunity Employer. The company promotes and supports a diverse workforce at all levels across the Company. The Company ensures that its associates or potential hires, third-party support staff and suppliers are not discriminated against, directly or indirectly, as a result of their colour, creed, cast, race, nationality, ethnicity or national origin, marital status, pregnancy, age, disability, religion or similar philosophical belief, sexual orientation, gender or gender reassignment, etc We are looking for a skilled and experienced Data Engineer with 3 to 5 years of experience to design, build, and optimize scalable data pipelines and infrastructure. The ideal candidate will work closely with data scientists, analysts, and software engineers to ensure reliable and efficient data delivery throughout our data ecosystem. Key Responsibilities: Design, implement, and maintain robust data pipelines using ETL/ELT frameworks. Build and manage data warehousing solutions (e.g., Snowflake, Redshift, BigQuery). Optimize data systems for performance, scalability, and cost-efficiency. Ensure data quality, consistency, and integrity across various sources. Collaborate with cross-functional teams to integrate data from multiple business systems. Implement data governance, privacy, and security best practices. Monitor and troubleshoot data workflows and conduct root cause analysis on data-related issues. Automate data integration and validation processes using scripting languages (e.g., Python, SQL). Work with DevOps teams to deploy data solutions using CI/CD pipelines. Required Skills & Qualifications: Bachelor's or Masters degree in Computer Science, Engineering, Data Science, or a related field. 3 to 5 years of experience in data engineering or a similar role. Strong proficiency in SQL and at least one programming language (Python, Java, or Scala). Experience with cloud platforms (AWS, Azure, or GCP). Hands-on experience with data pipeline tools is added bonus(e.g., Apache Airflow, Luigi, DBT). Proficient in working with relational and NoSQL databases. Familiarity with big data tools (e.g., Spark, Hadoop) is a plus. Good understanding of data architecture, modeling, and warehousing principles. Excellent problem-solving and communication skills. Preferred Qualifications: Certifications in cloud platforms or data engineering tools. Experience with containerization (Docker, Kubernetes). Knowledge of real-time data processing tools (Kafka, Flink). Exposure to data privacy regulations (GDPR, HIPAA)