Senior Data Engineer

Job not on LinkedIn

🕒 3 days ago

🇮🇳 India – Remote

⏰ Full Time

🟠 Senior

🚰 Data Engineer

👻 Ghost score 12%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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SRM Technologies

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 1998

📦 Logistics

💼 Consulting

🏭 Manufacturing

Logistics • Consulting • Manufacturing

SRM Technologies is a leading provider of Product Engineering, Automotive Solutions, and Digital Transformation services. With over 25 years of experience, the company specializes in mobility solutions, cloud technologies, data analytics, and artificial intelligence to help enterprises enhance their operational efficiency and innovate their product offerings. SRM Tech focuses on diverse industries such as automotive, healthcare, consumer and retail, telecommunications, and education, leveraging technology to drive business success and agility.

📋 Description

• Design, develop, test, and maintain scalable ETL/ELT data pipelines • Develop production-quality data-processing solutions using Python and PySpark • Build reusable frameworks and components for ingestion, transformation, validation, and data publishing • Process large structured, semi-structured, and distributed datasets • Implement incremental and batch-processing patterns • Design and develop scalable Snowflake data solutions, including SQL transformations, data models, views, and reusable data structures • Optimize Snowflake workloads for performance, scalability, and cost • Troubleshoot Snowflake performance and data-quality issues • Build and maintain modular dbt transformation pipelines, tests, documentation, and deployment practices • Design and implement Apache Iceberg data-lake and lakehouse solutions • Work with partitioning, schema evolution, incremental processing, and table maintenance • Integrate Iceberg datasets with Spark and AWS data-processing services • Design and implement cloud-native AWS data solutions using services such as S3, Glue, EMR, and Lambda • Implement secure AWS IAM access patterns, monitor workloads, and troubleshoot operational issues • Diagnose and optimize Spark/PySpark jobs, SQL queries, Snowflake workloads, and data pipelines • Implement automated data-quality checks, logging, monitoring, exception handling, and reconciliation • Follow data security, governance, lineage, and access-control standards • Write clean, modular, reusable, testable, and maintainable code • Perform code reviews, implement testing, use Git and CI/CD, and maintain technical documentation • Drive complex data-engineering requirements from design through production deployment • Participate in architecture discussions and recommend implementation approaches • Troubleshoot production and performance issues • Mentor junior and mid-level data engineers • Collaborate with Architects, Product Owners, Business Analysts, Data Scientists, QA, DevOps, and application teams • Translate business and data requirements into scalable technical solutions • Identify technical risks and recommend improvements

🎯 Requirements

• 8+ years of overall Data Engineering experience • Strong hands-on experience building enterprise-scale cloud data platforms and pipelines • Strong hands-on expertise in Python, PySpark, Snowflake, dbt, Apache Iceberg, AWS, and advanced SQL • Experience with data engineering, ETL/ELT, data lake/lakehouse architecture, and high-volume data processing • Experience with Snowflake performance and cost optimization • Experience with dbt models, tests, macros, documentation, and deployment practices • Experience with Apache Iceberg partitioning, schema evolution, incremental processing, and table optimization • Experience with AWS data services and secure access patterns using IAM • Experience with Spark/PySpark optimization and troubleshooting • Experience with data modeling and dimensional modeling • Experience with data quality frameworks and automated validation • Experience with Git-based version control, testing, code reviews, CI/CD, and production support • Experience with data security, governance, lineage, and access controls • Experience working in Agile delivery environments • Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related discipline is preferred • AWS and/or Snowflake certification is an added advantage

🏖️ Benefits

• Remote work arrangement • AWS and/or Snowflake certification is an added advantage