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Responsibilities Data Engineering & Pipelines Build and maintain data ingestion pipelines from APIs and other data sources Write efficient Python and SQL for data transformation and processing Support ETL/ELT workflows, microservices and ensure timely data availability Troubleshoot pipeline failures and assist in performance improvements Marketing Data Support Assist in ingestion and modeling of data from Meta Ads and similar platforms Help create datasets for: o Campaign performance reporting o Lead funnel tracking Develop familiarity with: o Campaign structure (campaign/ad set/ad level) o Basic performance metrics (CTR, CPC, CPA) o Conversion tracking concepts Business Collaboration Work with marketing and analytics teams to understand data requirements Support analysis related to lead quality and campaign performance Help translate business needs into data queries and datasets Data Quality & Maintenance Implement basic data validation checks Monitor pipelines and resolve data issues Maintain documentation for pipelines and datasets Required Skills & Qualifications Core Technical Skills Proficiency in Python (data processing, API handling) Strong SQL skills Experience with data ingestion from APIs (basic handling of pagination, retries) Familiarity with workflow orchestration tools (e.g., Airflow or similar) Exposure to cloud data warehouses (BigQuery, etc.) Ad Platform Exposure Basic understanding of Meta Ads platform concepts Familiarity with: Marketing metrics (CTR, CPC, conversions) Lead generation and funnel basics Willingness to learn deeper AdTech concepts Soft Skills Good problem-solving and debugging skills Ability to work in a collaborative, cross-functional environment Clear communication of technical work and issues Good to Have Exposure to other marketing platforms (Google Ads, etc.) Experience with tools like dbt or similar transformation frameworks Understanding of event tracking (GA4, etc.) What Success Looks Like Reliable execution of data pipelines with minimal supervision Accurate and timely delivery of marketing datasets Growing understanding of marketing data and business use cases Effective collaboration with senior engineers and stakeholders Perks: Day off on the 3rd Friday of every month (one long weekend each month) Monthly Wellness Reimbursement Program to promote health well-being Monthly Office Commutation Reimbursement Program Paid paternity and maternity leaves .
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.