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Job Description : Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics. Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and GCP ‘big data’ technologies. Create and maintain optimal data pipeline architecture. Assemble large, complex data sets that meet functional / non-functional business requirements. Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc. Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs. Keep our data separated and secure across national boundaries through multiple data centers and GCP regions. Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader. Work with data and analytics experts to strive for greater functionality in our data systems. Qualifications: Bachelor's degree or higher - in Computer Science, Statistics, Informatics, Information Systems or another quantitative field 2+ years of experience in Data Engineer role (Junior - Mid Level) 5+ years of experience in Data Engineer role (Mid - Senior Level) Experience with big data tools: Hadoop, Spark, Kafka, etc. Experience with relational SQL and NoSQL databases, including Postgres and Firestore. Experience with data pipeline and workflow management tools: Airflow, etc. Experience with GCP cloud services: Compute Engine, Cloud Function, Cloud Dataproc, Cloud SQL, BigQuery Experience with stream-processing systems: GCP Cloud Composer is a plus Experience with object-oriented/object function scripting languages: Python, Java, etc. Advanced SQL expertise with relational databases and query optimization Proven experience designing and optimizing large-scale “big data” pipelines, architectures, and datasets Track record of root-cause analysis on internal and external data to answer business questions Demonstrated success manipulating and extracting value from large, disconnected datasets Experience partnering with cross-functional teams in fast-paced environments Strong project management and organizational capabilities
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.