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Designing implementing Data Pipelines Frameworks to provide a better developer experience for our dev teams. Helping other PODs in IDfy define their data landscape and onboarding them onto our platform. Keep abreast of the latest trends and technologies in Data Engineering, GenAI, and Natural Language Query. Set up logging, monitoring, and alerting mechanisms for better visibility into data pipelines and platform health. Automate repetitive data tasks to improve efficiency and free up engineering bandwidth. Maintain technical documentation to ensure knowledge sharing and onboarding efficiency. Troubleshoot and resolve bottlenecks in data processing, ingestion, and transformation pipelines. We Are the Perfect Match If You Have experience creating and managing large-scale data ingestion pipelines using the ELT (Extract, Load, Transform) model. In your current role, take ownership of defining data models, transformation logic, and data flow. Are proficient in Logstash, Apache BEAM Dataflow, Apache Airflow, ClickHouse, Grafana, InfluxDB/VictoriaMetrics, and BigQuery. Strong understanding and hands-on experience with data warehouses, with at least 3 years of experience in any data warehousing stack. Have a keen eye for data and can derive meaningful insights from it. Understand product development methodologies; we follow Agile. Have experience with Time Series Databases (we use InfluxDB VictoriaMetrics) and alerting/anomaly detection frameworks (preferred but not mandatory). Are familiar with visualization tools such as Metabase, Power BI, or Tableau. Have experience developing software in the cloud (GCP/AWS is preferred, but hands-on experience is not mandatory). Are passionate about exploring new technologies and enjoy sharing your knowledge through technical blogs.
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.