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About CACI Data Engineering CACI has implemented a Data Platform that supports and enables a Data Mesh organisation. It uses AWS technology to provide a unified experience across AWS services to deliver an open federated Lakehouse, and a unified User Experience. The Data Platform focusses on enabling decentralised management, processing, analysis and delivery of data, while enforcing corporate wide federated governance on data, and project environments across business domains. The goal is to empower multiple teams to create and manage high integrity data and data products that are analytics and AI ready and consumed internally and externally. Data Engineers will be part of a community of data engineers and are often embedded in different business units to develop data pipelines and products, maintaining these for use in consulting engagements and service delivery to clients. Data Engineers will work with the platform, corporate standards and processes. In a business that values continuous improvement, data engineers are expected to contribute to improving the wider data engineering capability in the business. What does a Data Engineer do A Data Engineer partners closely with business units to maintain existing cloud data architectures, as well as assess, design and execute the migration of their existing cloud and on premise/desktop data products and workflows onto a modern cloud data platform This involves understanding current data architectures, dependencies and transformation logic, and translating that into cloud native solutions in harmony with the Company data platform, governance and strategy. The Senior Data Engineer will need skills in developing data pipelines that operate across a medallion architecture, with an obsession on data quality and integrity of the products and processes and always considering the cost benefit of different approaches. This will need attention to technical rigour and pragmatic delivery. You will leverage skills in AWS Services such as Glue, EMR, S3, MWAA (Apache Airflow), Step Functions, Redshift, Sagemaker Unified Studio, as well as an understanding of traditional RDBMS in Postgres, Oracle and SQL Server. SQL, Python and PySpark will be essential in this role. Experience with IaC such as cloud formation will be an important skill to have, or to develop. You will be able to design architectures and create re-useable solutions to reflect the business needs. It is important that we create Patterns that we can reuse for multiple products and services, so that we are note designing new solutions for every need. Some products will have linear data ingest, transformation and publishing requirements, others will require extensive analytical work in the pipelines, including machine learning, deep learning and the potential to integrate more unstructured data as new products are built and matured. Responsibilities will include: Collaborating across CACI departments to develop and maintain data products and the data platform Designing and implementing data processing environments and integrations using AWS PaaS such as Glue, S3, Lambda, Fargate, EMR, Sagemaker, Redshift, Aurora and Snowflake Data architecture and data modelling across full data lifecycles, as well as more detailed modelling requirements of databases and data products. Building data processing and analytics pipelines as code, using python, SQL, PySpark, Spark, CloudFormation, Lambda, Step Functions, Apache Airflow Designing and applying security and access control architectures to secure sensitive data Enabling business units by working with them to deliver complete and manageable solutions; while providing support and expert advice. You will have: Strong experience and knowledge of data architectures implemented in AWS using native AWS services such as S3, DataZone, Glue, EMR, Sagemaker, Aurora and Redshift using Python, PySpark, and SQL Experience developing and administrating databases, data platforms and solutions Good coding discipline in terms of style, structure, versioning, documentation and unit tests A well developed understanding of a data mesh organisation, as well as Master and Reference Data Management Experience migrating legacy to modern, as well as modern to modern. Knowledge and experience of relational databases such as Postgres, Redshift Experience using Git for code versioning, and lifecycle management Experience operating to Agile principles and ceremonies Hands-on experience with CI/CD tools such as GitLab Strong problem-solving skills and ability to work independently or in a team environment. Excellent communication and collaboration skills. A keen eye for detail, and a passion for accuracy and correctness in numbers Whilst not essential, the following skills would also be useful: Experience using Jira, or other agile project management and issue tracking software Experience with Spatial Data Proc .
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.