Big Data Analyst - Hadoop & Spark Infrastructure

Job Summary
The Elite Job is seeking a highly skilled  Big Data Analyst  with expertise in  Hadoop and Spark  to join our dynamic analytics team. The successful candidate will leverage advanced big data technologies to process, analyze, and interpret vast datasets, providing actionable insights that drive strategic business decisions. This role requires a proactive, detail‑oriented professional who thrives in a fast‑paced environment and is passionate about transforming raw data into meaningful business outcomes.

Key Responsibilities

Design, develop, and maintain scalable  Hadoop and Spark‑based data pipelines  for large‑scale data processing.

Extract, transform, and load (ETL) complex datasets from multiple structured and unstructured sources.

Collaborate with data engineers, data scientists, and business stakeholders to understand data requirements and provide analytical solutions.

Optimize and troubleshoot big data workflows to ensure high performance, reliability, and data accuracy.

Implement and enforce data governance, quality standards, and best practices.

Perform advanced data analysis, pattern recognition, and predictive modeling to support strategic initiatives.

Prepare detailed reports and visualizations to communicate findings to both technical and non‑technical stakeholders.

Stay current with emerging big data technologies, trends, and best practices to continuously enhance infrastructure and analytics capabilities.

Required

Skills and Qualifications

Strong hands‑on experience with  Hadoop ecosystem tools  (HDFS, Hive, Pig, HBase).

Expertise in  Apache Spark  for distributed data processing.

Proficiency in programming languages such as  Python, Java, or Scala .

Experience with  SQL and No

SQL databases .

Familiarity with  data warehousing, ETL processes, and data modeling techniques .

Solid understanding of  big data architecture, frameworks, and cloud platforms  (AWS, Azure, or GCP).

Ability to work with large datasets, perform data cleaning, and ensure data quality.

Excellent problem‑solving, analytical, and critical‑thinking skills.

Experience

Minimum of  3–5 years of experience  in big data analytics, preferably in roles focusing on Hadoop and Spark infrastructure.

Proven track record of delivering successful data‑driven projects in a complex, enterprise environment.

Prior experience in financial services, e‑commerce, or technology sectors is a plus.

Working Hours

Full‑time position.

Flexible working hours with options for remote or hybrid arrangements.

Occasional extended hours may be required to meet project deadlines or support global teams.

Knowledge, Skills, and Abilities

Strong analytical mindset with an ability to translate data insights into business value.

Excellent communication and collaboration skills to work effectively with cross‑functional teams.

Ability to manage multiple priorities in a fast‑paced, dynamic environment.

Detail‑oriented with strong organizational and documentation skills.

Self‑motivated with a continuous learning attitude toward new technologies and tools.

Benefits

Competitive salary and performance‑based incentives.

Health, dental, and vision insurance coverage.

Flexible remote work options and generous paid time off.

Professional development opportunities, including training and certification support.

Collaborative and inclusive work culture that values innovation and creativity.

Why Join The Elite Job
At The Elite Job, we empower our employees to leverage cutting‑edge technology and deliver data‑driven solutions that make a real impact. You will be part of a forward‑thinking organization where innovation, learning, and growth are encouraged. Join a team of passionate professionals who value creativity, collaboration, and excellence in all that we do.

How to Apply

Interested candidates are invited to submit their  resume and cover letter  highlighting relevant experience to us. Please include  Big Data Analyst – Hadoop & Spark  in the subject line. Shortlisted candidates will be contacted for further assessment and interviews.

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