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Responsibilities - Contribute towards supporting the build/implementation of data ingestion and curation processes developed using Big data tools such as Spark (Scala/python), Hive, HDFS, Kafka, Pig, Spark, HDFS, Oozie, Sqoop, Flume, Zookeeper, Kerberos, Sentry, Impala, CDP 7.x etc. under the guidance of Big Data Engineers. - Support the ingestion of huge data volumes from various platforms for Analytics needs and prepare high-performance, reliable, and maintainable ETL code with support/review guidance of senior team members. - Provide relevant support in monitoring performance and advising any necessary infrastructure changes to senior team members for their review inputs. - Understand the defined data security principals and policies developed using Ranger and Kerberos. - Gain broader understanding on how to support application developers and progressively work on effective big data application development using cutting edge technologies. - Collaborate with Business systems analyst, technical leads, Project managers and business/operations teams in building data enablement solutions across different LOBs and use cases basis - Understand & support the creation of reusable frameworks which will optimize the development effort involved. - Contribute towards supporting the build/implementation of data ingestion and curation processes developed using Big data tools such as Spark (Scala/python), Hive, HDFS, Kafka, Pig, Spark, HDFS, Oozie, Sqoop, Flume, Zookeeper, Kerberos, Sentry, Impala, CDP 7.x etc. under the guidance of Big Data Engineers. - Support the ingestion of huge data volumes from various platforms for Analytics needs and prepare high-performance, reliable, and maintainable ETL code with support/review guidance of senior team members. - Provide relevant support in monitoring performance and advising any necessary infrastructure changes to senior team members for their review inputs. - Understand the defined data security principals and policies developed usi .
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.