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As a Senior Data Engineer at SkillLane, you will design, build, and optimize scalable data pipelines and data platforms that power business intelligence, analytics, and AI initiatives. You will work closely with cross-functional teams to ensure high-quality, reliable, and secure data while driving data engineering best practices to support business growth and data-driven decision-making. Job Descriptions: Leading the development and implementation of streaming and batch data pipelines to extract, transform, and load data from various sources into our data lakes/data warehouse. Implement self-service tools in the data platform (orchestration tools and data quality tools) Implement a data validation process to improve data quality in data pipelines Monitor the data platform cluster (Kubernetes) Implement a data observability process to monitor data pipelines Implement data lineage to tracking data movement Implement data dictionary, relationship and its interpretation Developing and maintaining data processing and analysis frameworks Ensuring data security, privacy, and compliance with relevant regulations and policies Collaborating with data analysts to understand data requirements and perform database design based on data understanding and requirements with consideration for performance Manipulating complex data from different sources (MySQL, PostgreSQL, MongoDB, Excel, CSV, and Google Sheets) Monitoring data quality and troubleshooting data-related issues Identifying and implementing process improvements to enhance the efficiency and effectiveness of our data systems Requirements: Bachelor's or Master's degree in Computer Science, Engineering, or related field 5+ years of experience in data engineering or related field Experience with streaming and batch data processing, ETL, and data warehousing Experience in Cloud-based data platforms (Azure, AWS, GCP, or others) Experience in Git, Docker, BigQuery, Airflow Experience with databases (e.g., MySQL, PostgreSQL, MongoDB) Strong programming skills (SQL, Python) Strong understanding of coding standards and testing Experience in managing projects and leading teams Have a growth mindset and a willingness to learn new things or share knowledge with others Ability to self-learn Understand Kubernetes is a plus Understanding the data lineage concept is a plus Understand data observability concept is a plus Understand data mesh concept is a plus
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.