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Assistant Manager - Data Engineer We are looking for an experienced Data Engineer to design, build, and maintain scalable data pipelines and infrastructure that power analytics, reporting, and machine learning initiatives across the organization. The ideal candidate has a strong foundation in data modeling, distributed systems, and cloud-based data platforms, with a track record of delivering reliable, high-performance data solutions. Key Responsibilities ● Design, build, and optimize scalable ETL/ELT pipelines to ingest, transform, and load data from diverse sources (databases, APIs, streaming platforms, third-party systems) ● Develop and maintain data warehouse/data lake architectures, ensuring data quality, consistency, and reliability ● Collaborate with data scientists, analysts, and product teams to understand data requirements and deliver well-structured, accessible datasets ● Build and maintain batch and real-time streaming data pipelines using tools like Apache Spark, Kafka, or Airflow ● Implement data quality checks, monitoring, and alerting to ensure pipeline reliability and data integrity ● Optimize database and query performance for large-scale datasets ● Design and maintain data models (conceptual, logical, physical) and schemas that support analytics and application needs ● Work with cloud platforms (AWS/Azure/GCP) to manage data infrastructure, storage, and compute resources ● Implement and enforce data governance, security, and compliance best practices ● Participate in code reviews, CI/CD pipeline development, and infrastructure-as-code practices ● Document data pipelines, architecture, and processes for team knowledge sharing ● Troubleshoot and resolve production data pipeline issues in a timely manner Required Skills & Qualifications ● Bachelor's degree in Computer Science, Engineering, or a related field ● 4–6 years of hands-on experience as a Data Engineer or in a similar role ● Strong programming skills in Python and/or Scala; solid SQL expertise ● Experience with ETL/ELT tools and orchestration frameworks (Apache Airflow, dbt, Luigi, or similar) ● Hands-on experience with big data technologies (Apache Spark, Hadoop, Kafka) ● Proficiency with relational databases (PostgreSQL, MySQL, SQL Server) and NoSQL databases (MongoDB, Cassandra, DynamoDB) ● Experience working with cloud data platforms and services (AWS Redshift/Glue/S3, Azure Data Factory/Synapse, GCP BigQuery/Dataflow) ● Solid understanding of data modeling concepts — entity relationships, cardinality, normalization, and dimensional modeling (star/snowflake schemas) ● Experience with data warehousing solutions (Snowflake, Redshift, BigQuery, Databricks) ● Familiarity with version control (Git) and CI/CD practices ● Understanding of data governance, security, and privacy best practices (GDPR, data masking, access controls) ● Strong problem-solving skills and ability to work with large, complex datasets ●
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.