Baker Hughes is hiring for an exciting opportunity that could shape the future of your analytics career. The company is currently recruiting professionals for the Baker Hughes Data Analytics role based in Bangalore. If you’re passionate about data engineering, predictive analytics, and big data tools, this role is ideal for you. With a competitive salary, flexible work model, and exposure to enterprise-level projects, it’s a role you won’t want to miss.
About the Company
Baker Hughes is a global energy technology company dedicated to making energy safer, cleaner, and more efficient. With operations in over 120 countries and over a century of innovation, the company continues to lead the way in digital transformation across the industrial and energy sectors. Known for its inclusive work culture and commitment to technological advancement, Baker Hughes empowers employees to bring innovative solutions to real-world challenges.
Role Details
- Position: Data Engineer – Data Analytics
- Location: Bangalore, India
- Work Type: Hybrid (Remote flexibility based on team needs)
- Qualification: Any Graduate
- Experience: Minimum 2 years
- Salary: Up to ₹10 LPA
- Industry: Digital Technology
Key Responsibilities
- Develop, transform, and manage large-scale datasets for analysis
- Design data models and build scalable data pipelines
- Perform integration of multi-source data formats into a unified structure
- Work closely with data scientists, software engineers, and product managers
- Implement big data solutions using modern technologies and frameworks
- Translate business needs into actionable data-driven solutions
- Ensure high-performance data infrastructure with robust monitoring
- Collaborate with cross-functional teams to enhance data capabilities
- Maintain compliance with data integrity and security standards
Eligibility Criteria
- Bachelor’s degree in Computer Science, Engineering, or related field
- Minimum 2 years of relevant experience in data engineering or analytics
- Proficiency in Python, Perl, or Pig scripting
- Strong understanding of data modeling, metadata, and ETL processes
- Familiarity with data storage architecture and data profiling
- Ability to interpret business problems and translate them into data requirements
- Excellent verbal and written communication skills
- Strong analytical mindset and curiosity for innovation
Salary and Perks
- Salary up to ₹10 LPA depending on experience
- Health and medical insurance coverage
- Life and disability protection policies
- Flexible work hours and remote work options
- Employee incentive programs and financial planning support
- Career growth programs, skill development workshops
- Wellness initiatives and a balanced work-life environment
Work Setup
This role supports a hybrid model, offering a mix of work-from-home and office flexibility. Baker Hughes believes in empowering employees to deliver their best work from any location, while also maintaining a collaborative culture with cross-functional engagement.
Application Process
If you meet the qualifications and are ready to take your data analytics career to the next level, now is the perfect time to apply. Applications are open for a limited period. Selection is ongoing, so early applicants have a better chance of being shortlisted.
Apply Link – Baker Hughes Data Engineer – Data Analytics Jobs
Why Choose This Role?
Joining Baker Hughes means becoming part of a company that values innovation, employee growth, and impactful work. The Baker Hughes Data Analytics role is more than just a position—it’s an opportunity to build intelligent data solutions that help businesses worldwide make informed decisions. You’ll be surrounded by brilliant minds, receive mentorship, and be part of a team that thrives on creativity and collaboration.
Tips for Candidates
1) Master Your Tools – Polish your skills in ETL, Python, SQL, and data modeling before the interview.
2) Understand Business Impact – Learn how your role in analytics influences energy and industrial decisions.
3) Build a Strong Resume – Highlight your experience with large datasets, transformations, and data pipelines.
4) Focus on Communication – Be ready to explain technical concepts to non-technical stakeholders.
5) Prepare for Problem Solving – Expect scenario-based questions that test both logic and business awareness.