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Responsible for developing, optimizing, and maintaining business intelligence and data warehouse solutions with expertise in Google Cloud Platform (GCP). Lead the transition of legacy databases, data warehouses, and multi-cloud workloads to modern GCP architectures, ensuring secure, scalable, and efficient data processing. Enable self-service analytics, improve data accessibility, and provide stakeholders with impactful reporting and analytical insights to support strategic business decisions. Grade: T5Please note that the job will close at 12:00 AM on the Posting Close Date. Please submit your application before the closing date. What Your Main Responsibilities AreAccountabilities Data Pipeline Engineering Design, develop, and maintain scalable, reliable, and high-performance data pipelines to support growing data volumes and complexity.Build and manage APIs, data ingestion frameworks, and streaming/batch data processing solutions on Google Cloud Platform (GCP). Cloud Data Integration Integrate structured and unstructured data from multiple online and offline sources to create a unified view of customer, operational, and business data.Perform data acquisition, processing, transformation, analysis, and visualization to enable advanced analytics and personalization initiatives.Support migration and integration of legacy databases, on-premises data platforms, and other cloud environments into GCP. Data Quality & Governance Drive data quality, consistency, and readiness for enterprise analytics.Define, implement, and continuously improve data governance frameworks, standards, controls, and best practices.Establish data validation, monitoring, lineage, and metadata management processes across data platforms. Data Transformation & Engineering Design and implement ETL/ELT frameworks to cleanse, enrich, and transform data for analytical and operational consumption.Develop optimized data models and storage structures to support reporting, self-service analytics, machine learning, and business intelligence workloads. Data Enablement & Analytics Ensure enterprise-wide access to trusted, governed, and scalable data assets.Enable self-service analytics and support stakeholders with actionable insights through reporting, dashboards, and advanced analytical solutions.Partner with business and technology teams to drive data-driven decision making.Qualifications & SpecificationsBachelor's or Master's degree in Engineering, Computer Science, Mathematics, Statistics, or a related quantitative field.57 years of relevant Data Engineering experience.Strong programming skills in Python, PySpark, and SQL.Experience working with large-scale data platforms and distributed computing technologies including Spark, Hadoop, Hive, and Big Data ecosystems.Strong hands-on experience with Google Cloud Platform (GCP) services, including:BigQueryCloud StorageDataflowDataprocPub/SubCloud Composer (Airflow)BigQuery Data Transfer ServicesCloud Functions / Cloud RunLooker / Looker StudioExperience building modern data lake and data warehouse solutions on GCP.Hands-on experience with data orchestration, workflow management, and pipeline automation tools.Experience with DevOps and DataOps practices including:DockerCI/CDKubernetesTerraformGit-based deployment frameworksStrong experience in SQL development, data modeling, dimensional modeling, and performance optimization.Proficiency with enterprise ETL and data integration technologies such as Ab Initio, Informatica, DataStage, or equivalent platforms.Experience supporting or leading cloud migration and modernization initiatives, including migration from legacy data warehouses, on-premises environments, and other cloud platforms to GCP.Experience with BI and visualization platforms such as Power BI, Looker, Tableau, or equivalent (preferred).Google Cloud certifications such as:Professional Data EngineerProfessional Cloud ArchitectAssociate Cloud Engineer (Preferred)Experience working in Agile delivery environments.Strong stakeholder management, communication, and cross-functional collaboration skills.Preferred ExperienceCloud migration and modernization projects.Data warehouse and analytics platform transformation initiatives.Customer data, marketing analytics, pricing analytics, or revenue management domain experience.Experience mentoring junior engineers and driving engineering best practices.Experience Required: 57 years of relevant Data Engineering and Cloud Data Platform experience. What we are looking for Education: Bachelor's degree or equivalent in Computer Science, MIS, Mathematics, Statistics, or similar discipline. Master's degree or PhD preferred. Knowledge, Skills and Abilities Fluency in English Analytical Skills Accuracy & Attention to Detail Numerical Skills Planning & Organizing Skills Presentation Skills Data Modeling and Database Design ETL (Extract, Transform, Load) Skills Programming Skills FedEx was built on a philosophy that puts people
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.