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Role Description Key Responsibilities Lead the design and architecture of scalable big data solutions using Apache Spark and Hadoop ecosystem technologies. Own end-to-end development of batch and streaming data pipelines. Design, optimize, and tune Spark applications for performance, scalability, and reliability. Provide technical leadership for Hadoop components including HDFS, Hive, HBase, and YARN. Ensure data quality, data governance, security, and compliance standards are met. Lead real-time streaming solutions using Spark Structured Streaming and Kafka. Review code, conduct technical design reviews, and enforce engineering best practices. Collaborate with architects, product owners, and business stakeholders to translate requirements into technical solutions. Mentor and guide data engineers and developers. Support production deployments, monitoring, and incident resolution. Drive continuous improvement, automation, and adoption of recent big data technologies. Required Technical Skills Robust experience with Apache Spark (Spark SQL, DataFrames, Datasets, Structured Streaming). Hands-on experience with Hadoop ecosystem tools (HDFS, Hive, HBase, YARN). Advanced SQL and data modeling knowledge. Experience with data formats such as Parquet, ORC, and Avro. Knowledge of distributed systems and performance tuning. Experience with Kafka or similar messaging platforms. Solid programming skills in Python, Scala, or Java. Experience with CI/CD pipelines and DevOps practices. Cloud & Platform Experience Experience with cloud-based big data platforms such as AWS EMR/Glue, Azure Databricks/Synapse, or GCP Dataproc. Experience migrating Hadoop workloads to cloud-based platforms. Understanding of cloud security, cost optimization, and scalability best practices. Skills spark,cloud computing,data quality management,databricks, .
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.