Data Engineer

Company Name :<\/b><\/span><\/span><\/span>
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Job Title :<\/b><\/span><\/span><\/span>
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Data Engineer<\/span><\/span>
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Qualification :<\/b><\/span><\/span><\/span>
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Any graduation<\/span><\/span>
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Experience :<\/b><\/span><\/span><\/span>
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6 to 9 years<\/span><\/span>
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Must Have Skills :<\/b><\/span><\/span><\/span>
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Strong proficiency in SQL<\/span><\/span><\/b> and experience with relational databases (PostgreSQL, MySQL, SQL Server, Oracle).<\/span><\/span><\/span><\/span>
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• Hands -on experience with ETL/ELT pipelines<\/span><\/span><\/b> using tools like Airflow, ADF, Glue, or similar.<\/span><\/span>
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  • Expertise in big data technologies<\/span><\/span><\/b> such as Spark, Hadoop, Hive, or Kafka.<\/span><\/span>
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    • Programming experience in Python/Scala<\/span><\/span><\/b> for data processing and automation.<\/span><\/span>
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      • Experience with cloud data platforms<\/span><\/span><\/b> (AWS Redshift, Azure Synapse, GCP BigQuery, Snowflake, etc.)<\/span><\/span>
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Good to Have Skills :<\/b><\/span><\/span><\/span>
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Knowledge of <\/span><\/span>Data Modeling concepts<\/span><\/span><\/b> (Star Schema, Snowflake Schema, Normalization).<\/span><\/span><\/span><\/span>
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1. Experience with <\/span><\/span>Data Warehousing and Lakehouse architectures<\/span><\/span><\/b>.<\/span><\/span>
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2. Familiarity with <\/span><\/span>DevOps/DataOps tools<\/span><\/span><\/b> (Docker, Kubernetes, CI/CD, Git).<\/span><\/span>
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3. Experience with <\/span><\/span>stream -processing pipelines<\/span><\/span><\/b> (Spark Streaming, Kafka Streams).<\/span><\/span>
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4. Understanding of <\/span><\/span>data quality, data governance, and metadata management<\/span><\/span><\/b> frameworks.<\/span><\/span>
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Roles and Responsibilities :<\/b><\/span><\/span><\/span>
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Design, build, and maintain scalable ETL/ELT data pipelines<\/span><\/span><\/b> for batch and real -time processing.<\/span><\/span><\/span><\/span>
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• Develop and optimize data models, warehouse structures<\/span><\/span><\/b>, and storage solutions.<\/span><\/span>
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  • Integrate data from various internal and external data sources<\/span><\/span><\/b> ensuring reliability and accuracy.<\/span><\/span>
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    • Collaborate with analysts, data scientists, and business teams<\/span><\/span><\/b> to understand data needs.<\/span><\/span>
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      • Monitor and troubleshoot production data workflows<\/span><\/span><\/b>, ensuring high availability and performance.<\/span><\/span>
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        • Implement data quality checks, validation processes<\/span><\/span><\/b>, and governance practices.<\/span><\/span>
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          • Automate data ingestion, transformation, and workflow orchestration<\/span><\/span><\/b> using scripting and tools.<\/span><\/span>
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            • Optimize big -data processes<\/span><\/span><\/b> for performance, scalability, and cost efficiency.<\/span><\/span>
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              • Ensure adherence to security, compliance, and privacy standards<\/span><\/span><\/b> when handling data.<\/span><\/span>
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                • Document data flow diagrams, technical designs, and pipeline specifications<\/span><\/span><\/b>.<\/span><\/span>
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Location :<\/b><\/span><\/span><\/span>
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Bangalore , Hyberabad , Chennai , Mumbai, Pune<\/span><\/span>
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CTC Range :<\/b><\/span><\/span><\/span>
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18 to 24 LPA<\/span><\/span>
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Notice period :<\/b><\/span><\/span><\/span>
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Immediate to 15 days<\/span><\/span>
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Shift Timings :<\/b><\/span><\/span><\/span>
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General<\/span><\/span>
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Mode of Interview :<\/b><\/span><\/span><\/span>
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Virtual<\/span><\/span>
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Mode of Work :<\/b><\/span><\/span><\/span>
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Hybrid<\/span><\/span>
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Mode of Hire :<\/b><\/span><\/span><\/span>
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Permanent<\/span><\/span>
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Note :<\/b><\/span><\/span><\/span>
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