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About The Role In this role, you will contribute to building scalable and reliable data solutions on Google Cloud Platform, leveraging modern Big Data technologies and cloud-native services. You will work with batch and streaming data processing systems, helping organizations transform, manage, and unlock the value of their data. As part of a collaborative engineering team, you will participate in the full project lifecycle, from discovery and solution design to implementation and production deployment. Responsibilities Design, develop, and maintain scalable data pipelines for batch and streaming workloads Build and optimize data processing solutions using Python (must), SQL, Java, Apache Spark, and Databricks Create cloud-native data architectures leveraging GCP services including BigQuery, Dataflow, Cloud Composer, Pub/Sub, and Cloud Storage Implement data transformation, modeling, and analytics engineering practices using dbt and Dataform Collaborate with business stakeholders, architects, and engineering teams to translate data requirements into effective technical solutions Support development of modern data platforms and analytics solutions on GCP with GCP native services and/or Databricks Contribute to technical design discussions, architecture decisions and continuous improvement initiatives Ensure data quality, reliability and performance across data processing workflows Support end-to-end project delivery, including PoCs, MVPs, production deployments and platform enhancements Requirements 5+ years of professional experience in Big Data or Data Engineering Advanced expertise in Python and SQL (Java nice to have) for large-scale data processing and transformation Hands-on experience developing data solutions on Google Cloud Platform (GCP) Experience with Apache Spark and data processing frameworks such as Cloud Dataflow or Apache Beam Proven background building scalable solutions using Databricks and Lakehouse concepts Experience with orchestration tools such as Apache Airflow or Cloud Composer Knowledge of streaming technologies such as Apache Kafka or Google Cloud Pub/Sub Strong knowledge of BigQuery and modern cloud data architectures Experience with data transformation and modeling tools such as dbt and Dataform Strong analytical thinking, troubleshooting capabilities, and problem-solving skills Effective communication with both technical and non-technical stakeholders Upper-intermediate or higher level of English SoftServe is an equal opportunity employer. Qualified applicants will receive consideration regardless of race, color, ancestry, ethnicity, national origin, religion, sex, sexual orientation, gender identity or expression, age, citizenship, disability, health condition, marital or family status, veteran status, or any other characteristic protected by applicable law.
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.