Senior Data Engineer

🔥 20 hours ago

🇮🇳 India – Remote

⏰ Full Time

🟠 Senior

🚰 Data Engineer

👻 Ghost score 11%

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.

Apply Now

Find Similar Remote Jobs

Set Up Email Alert For New Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

Cummins Inc.

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1919

🏗️ Construction

💼 Consulting

🏥 Healthcare

💰 $75M Grant on 2024-07

Construction • Consulting • Healthcare

Cummins Inc. is a global power technology leader that designs, manufactures, and distributes a variety of engines and power systems solutions. They offer products that range from diesel and natural gas engines to hybrid and electric power systems, as well as components like turbochargers, fuel systems, and emissions solutions. With a strong emphasis on innovation, Cummins aims to reduce emissions and improve fuel efficiency. The company is dedicated to helping industries navigate the transition to cleaner energy through integrated power solutions suitable for diverse applications such as on-highway, marine, mining, and construction. Additionally, Cummins provides services including remote monitoring, diagnostics, and aftermarket support, reinforcing its commitment to sustainability and customer service excellence.

📋 Description

• Lead the design, development, deployment, and maintenance of data and analytics platforms • Design, develop, and automate distributed data ingestion and transformation solutions • Build reliable, scalable, and efficient ETL/ELT data pipelines • Design and implement data quality, validation, monitoring, and alerting frameworks • Implement data governance practices covering metadata, access, retention, compliance, and security • Design and implement physical data models, database structures, indexing, and table relationships • Develop and operate large-scale data storage and processing solutions across cloud and distributed platforms • Optimize data pipelines, Spark workloads, databases, and cloud infrastructure • Integrate enterprise application and source-system data, including real-time and event-driven processing • Implement CI/CD and DevOps practices for deployment, testing, and release management • Troubleshoot, test, validate, and continuously improve data pipelines and platform solutions • Collaborate with data scientists, analysts, architects, IT teams, and business stakeholders • Document data solutions, processes, designs, and technical information • Apply Agile methodologies such as Scrum and Kanban • Provide technical leadership and mentor less experienced team members

🎯 Requirements

• Bachelor’s degree or equivalent qualification in Computer Science, Information Technology, Engineering, Data Science, or another relevant technical discipline • Relevant equivalent professional experience may be considered • Relevant cloud or data engineering certifications are preferred • This position may require licensing or other requirements related to export controls or sanctions regulations • Strong technical leadership and decision-making skills • Strong problem-solving and analytical skills • Ability to translate complex technical concepts and stakeholder requirements into actionable data solutions • Strong understanding of data quality, governance, security, compliance, and data management principles • Advanced proficiency in Azure Databricks, Apache Spark, and distributed data processing frameworks • Strong expertise in enterprise-scale ETL/ELT and data ingestion pipeline design and development • Advanced proficiency in Python and Scala • Strong SQL skills • Strong experience with Azure data services, including Azure Databricks, ADLS, Azure Blob Storage, Azure Synapse Analytics, and Azure SQL Data Warehouse • Experience with Delta Lake, Apache Iceberg, Parquet, and ORC • Experience with Kafka or similar real-time streaming technologies • Experience implementing CI/CD pipelines and automated deployment processes • Strong knowledge of Git, Jenkins, testing methodologies, version control, and release management • Experience implementing data validation frameworks, monitoring solutions, and data quality controls • Knowledge of cloud security, access management, data governance, compliance, and regulatory requirements • 8+ years of hands-on experience in Data Engineering, Data Platform Engineering, Big Data, or a related discipline • 3+ years of experience leading technical teams, projects, or significant data engineering initiatives • Proven experience building and supporting large-scale cloud-based data ingestion, transformation, and analytics platforms • Experience developing end-to-end ETL/ELT solutions in Azure cloud environments • Experience delivering distributed data processing solutions using Spark and Databricks • Experience optimizing data pipelines, Spark workloads, databases, and cloud infrastructure • Experience working with data lake, data warehouse, and lakehouse architectures • Experience working within Agile software development methodologies • Experience processing and managing large datasets • Experience with Spark, Scala/Java, MapReduce, Hive, HBase, and Kafka or equivalent experience