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Our client, a rapidly expanding global technology partner, is looking for a highly skilled Senior Python Data Engineer to join their exceptional Technology and Development team. The role is in Kolkata. If you are passionate about demonstrating your expertise and thrive on collaborating with a group of talented engineers, then this role was made for you! At the heart of technology innovation, our client specializes in delivering cutting-edge solutions to clients across a wide array of sectors. With a strategic focus on finance, banking, and corporate verticals, they have earned a stellar reputation for their commitment to excellence in every project they undertake. They are searching for a senior engineer to strengthen their global projects team. They seek an experienced Senior Python Data Engineer with a strong background in building Extract, Transform, Load (ETL) processes and a deep understanding of AWS serverless cloud environments. As a vital member of the data engineering team, you will play a critical role in designing, developing, and maintaining data pipelines that facilitate data ingestion, transformation, and storage for our organization. Your expertise will contribute to the foundation of our data infrastructure, enabling data-driven decision-making and analytics. Key Responsibilities: ETL Pipeline Development: Design, develop, and maintain ETL processes using Python, AWS Glue, or other serverless technologies to ingest data from various sources (databases, APIs, files), transform it into a usable format, and load it into data warehouses or data lakes. AWS Serverless Expertise: Leverage AWS services such as AWS Lambda, AWS Step Functions, AWS Glue, AWS S3, and AWS Redshift to build serverless data pipelines that are scalable, reliable, and cost-effective. Data Modeling: Collaborate with data scientists and analysts to understand data requirements and design appropriate data models, ensuring data is structured optimally for analytical purposes. Data Quality Assurance: Implement data validation and quality checks within ETL pipelines to ensure data accuracy, completeness, and consistency. Performance Optimization: Continuously optimize ETL processes for efficiency, performance, and scalability, monitoring and troubleshooting any bottlenecks or issues that may arise. Documentation: Maintain comprehensive documentation of ETL processes, data lineage, and system architecture to ensure knowledge sharing and compliance with best practices. Security and Compliance: Implement data security measures, encryption, and compliance standards (e.g., GDPR, HIPAA) as required for sensitive data handling. Monitoring and Logging: Set up monitoring, alerting, and logging systems to proactively identify and resolve data pipeline issues. Collaboration: Work closely with cross-functional teams, including data scientists, data analysts, software engineers, and business stakeholders, to understand data requirements and deliver solutions. Continuous Learning: Stay current with industry trends, emerging technologies, and best practices in data engineering and cloud computing and apply them to enhance existing processes. Qualifications: Bachelor's or Master's degree in Computer Science, Data Science, or a related field. Proven experience as a Data Engineer with a focus on ETL pipeline development. Strong proficiency in Python programming. In-depth knowledge of AWS serverless technologies and services. Familiarity with data warehousing concepts and tools (e.g., Redshift, Snowflake). Experience with version control systems (e.g., Git). Strong SQL skills for data extraction and transformation. Excellent problem-solving and troubleshooting abilities. Ability to work independently and collaboratively in a team environment. Effective communication skills for articulating technical concepts to non-technical stakeholders. Certifications such as AWS Certified Data Analytics - Specialty or AWS Certified DevOps Engineer are a plus. Preferred Experience: .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.