Job Role: Senior Data Engineer
Salary: Rs 19.8 Lakhs per year (₹1.7L per month).
Location : Thiruvananthapuram, Kerala
Company: Nissan
Qualifications: Graduate
Experience: Minimum 5-7 years of experience
ABOUT NISSAN
Nissan Motor Co., Ltd. Is a renowned Japanese automobile manufacturer based totally in 1933 and based totally in Yokohama, Japan. The agency designs, produces, and markets numerous kinds of motors, on the facet of automobiles, vans, and SUVs. Known for its innovation and backbone to amazing, Nissan has pioneered enhancements in car generation, inclusive of electric cars (EVs) with the famous Nissan Leaf.
The company operates globally, with production facilities in various international locations and a robust presence in superior and developing markets. Nissan is also part of the Renault-Nissan-Mitsubishi Alliance, a strategic partnership aimed toward fostering collaboration and taste in economies of scale. With a focal point on sustainability and technological development, Nissan continues to push the bounds of automobile engineering and stays a large player within the global automobile company.
Job Description
As a Senior Data Engineer, you may design, increase, and maintain data pipelines and architectures to assist superior analytics and commercial enterprise intelligence. You’ll work carefully with information scientists, analysts, and different stakeholders to make sure records are integrity, scalability, and performance. Your duties encompass optimizing facts processing, imposing ETL approaches, and coping with massive datasets. Strong expertise in SQL, Python, and big records technologies (e.g., Hadoop, Spark) is needed. You’ll additionally mentor junior engineers and make contributions to information method and governance efforts to align with organizational goals.
Qualifications and Skills for a Senior Data Engineer:
Educational Background:
- Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related subject. Advanced tiers or certifications in facts engineering or related regions are a plus.
Experience:
- Extensive experience (commonly five years) in facts engineering or a comparable role, demonstrating deep expertise in facts structure, database control, and statistics pipeline improvement. (Senior Data Engineer)
- Proven enjoy with large-scale records processing, ETL strategies, and running with huge information technologies.
Technical Skills:
- Programming Languages: Proficiency in SQL and programming languages which include Python, Java, or Scala. Experience with scripting and automation.
- Big Data Technologies: Hands-on revel in with large records frameworks like Apache Hadoop, Apache Spark, Apache Flink, or similar technologies.
- Data Warehousing Solutions: Familiarity with facts warehousing platforms which include Amazon Redshift, Google BigQuery, Snowflake, or conventional databases like PostgreSQL, MySQL, or Oracle.
- Data Modeling: Strong abilities in records modeling, schema layout, and optimization for each relational and NoSQL database.
- ETL Tools: Experience with ETL gear and platforms which includes Apache NiFi, Talen, Informatica, or similar.
- Cloud Platforms: Proficiency with cloud services and systems like AWS, Google Cloud Platform, or Microsoft Azure, including services associated with facts storage and processing.
- Data Modeling: Strong abilities in records modeling, schema layout, and optimization for each relational and NoSQL database.
Analytical Skills:
- Ability to investigate complex statistics sets and provide actionable insights.
- Strong problem-solving abilities and the capacity to troubleshoot records pipeline troubles and optimize performance.
Soft Skills:
- Excellent communique talents, with the capability to bring technical ideas to non-technical stakeholders correctly.
- Strong collaboration and teamwork abilities, with enjoy operating in cross-practical groups. (Senior Data Engineer)
- Leadership capabilities, inclusive of mentoring junior engineers and contributing to group development and exceptional practices.
Project Management:
- Experience with agile methodologies, venture control tools, and strategies to control facts tasks correctly.
- Proven capacity to prioritize responsibilities, manage more than one initiative simultaneously, and meet cut-off dates.
Data Governance and Compliance:
- Knowledge of facts governance frameworks, statistics privacy laws (e.g., GDPR, CCPA), and exceptional practices for making sure facts are safe and compliant.
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