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Job Description & How to Apply Below
Senior Data Engineer / Big Data Engineer
Experience:
10 to 12 Years
Location:
Mumbai, Pune, Chennai, Bangalore, Hyderabad
Job Description
- We are seeking an experienced Senior Data Engineer / Big Data Engineer with strong expertise in Databricks and Apache Flink to design, develop, and optimize large-scale data processing systems and real-time streaming pipelines. The ideal candidate should possess hands-on experience in big data ecosystems, distributed computing, and enterprise-grade data platforms to support scalable analytics and business intelligence initiatives.
Key Responsibilities
- Design, develop, and maintain scalable batch and real-time data pipelines using Databricks and Apache Flink.
- Build and optimize data processing workflows for high-volume structured and unstructured datasets.
- Develop streaming and event-driven architectures for real-time analytics and processing.
- Work with large-scale distributed systems and big data frameworks to ensure performance, scalability, and reliability.
- Design data ingestion, transformation, enrichment, and orchestration processes.
- Collaborate with cross-functional teams including data architects, business stakeholders, engineering teams, and analytics teams to deliver data solutions.
- Monitor, troubleshoot, and optimize performance of big data platforms and streaming applications.
- Implement best practices for data governance, data quality, security, and compliance.
- Participate in architecture discussions and contribute to technical design decisions.
- Mentor junior engineers and support technical leadership initiatives where required.
Required
Skills & Qualifications
- 10+ years of experience in Data Engineering / Big Data technologies.
- Strong hands-on experience with Databricks and Apache Flink.
- Expertise in big data technologies such as Apache Spark, PySpark, Hadoop, Kafka, Hive, HDFS, or related frameworks.
- Experience building real-time streaming data pipelines and event-driven architectures.
- Strong understanding of distributed systems, ETL/ELT frameworks, and large-scale data processing.
- Proficiency in SQL and programming languages such as Python, Scala, or Java.
- Experience with data lakes, lakehouse architectures, and cloud-based data platforms.
- Strong problem-solving skills and ability to work in a fast-paced environment.
Preferred Skills
- Experience with cloud platforms such as Amazon Web Services, Microsoft Azure, or Google Cloud.
- Exposure to CI/CD pipelines, orchestration tools, and Dev Ops practices.
- Experience with performance tuning, monitoring, and optimization of streaming systems.
- Understanding of data governance and security frameworks.
Good to Have
- Exposure to data warehousing and analytics platforms.
- Certification in Databricks, cloud platforms, or big data technologies.
- Experience in enterprise-scale data modernization or transformation programs.
Soft Skills
- Strong communication and stakeholder management skills.
- Analytical mindset with strong troubleshooting capabilities.
- Ability to work independently and collaborate across teams
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