Title: Senior Big Data Engineer (R-19335) Location: Hyderabad - India Workplace: hybrid Category: Technology Job Description: Shape the Future with Dun & Bradstreet At Dun & Bradstreet, we believe data has the power to create a better tomorrow. As a global leader in business decisioning data and analytics, we help companies worldwide grow, manage risk, and innovate. For over 180 years, businesses have trusted us to turn uncertainty into opportunity. We’re a diverse, global team that values creativity, collaboration, and bold ideas. Are you ready to make an impact and help shape what’s next? Join us! Explore opportunities at dnb.com/careers. Designation: Senior Software Engineer – Big Data Location: Hyderabad About Us: We are a global organization driven by a diverse community of professionals who bring unique experiences and perspectives to everything we do. Whether working from a corporate office or remotely, we stay connected by listening to our customers and collaborating on impactful solutions. Our products and services power businesses of all sizes, across industries. At the core of our operations are our values: being data-inspired, relentlessly curious, and inherently generous. These values guide our decisions, shape our culture, and define how we work together. Role Overview: We are looking for a Senior Software Engineer – Big Data to design, build, and optimize modern data platforms and pipelines. This role requires strong expertise in big data technologies, cloud environments, and data engineering best practices, with a focus on scalability, performance, and innovation. Key Responsibilities : - Design, build, deploy, and document scalable data pipelines within big data ecosystems - Develop ETL/ELT pipelines using modern data processing frameworks and tools - Work with data lake architectures and modern data warehousing concepts such as virtual data warehouses and push-down analytics - Build and optimize data solutions using file formats such as Parquet, Iceberg, and Delta - Develop high-performance solutions using Python, Databricks, and Apache Spark - Work with cloud infrastructure, primarily on GCP Design and manage relational databases including DB2, Oracle, and SQL Server with strong SQL expertise - Implement workflow scheduling and orchestration using Apache AirflowManage big data clusters including installation, configuration, monitoring, security, resource allocation, and performance tuning - Create detailed design documents and proof of concepts for new capabilities - Collaborate with platform and infrastructure teams to deploy solutions into production - Optimize workloads, manage multi-tenant environments, and ensure SLA adherence - Participate in planning, data science initiatives, and continuous platform improvement Key Requirements: - Minimum 8 years of experience in ETL/ELT technologies - 4+ years of hands-on experience with big data technologies such as Databricks and Apache Spark - Minimum 6 years of experience working with cloud platforms, preferably GCP - Strong programming expertise in Python - Experience with relational databases and complex SQL development - Exposure to NoSQL and graph databases is a plus - Experience with access control mechanisms such as role-based and attribute-based access - Familiarity with BI tools such as Tableau, Power BI, or Looker - Hands-on experience managing and deploying cloud-based solutions - Experience working in a global environment and DevOps model is an advantag Notice to Applicants: Please be advised that this job posting page is hosted and powered by Lever, a subsidiary of Employ Inc. Your use of this page is subject to Employ's Privacy Notice and Cookie Policy, which governs the processing of visitor data on this platform.

Working at Atlassian Atlassians can choose where they work - whether in an office, from home, or a combination of the two. That way, Atlassians have more control over supporting their family, personal goals, and other priorities. We can hire people in any country where we have a legal entity. Our Product DE organization is looking for a Senior Data Engineer reporting to Senior Data Engineering Manager. You will be responsible for designing premier data architecture and solutions that drive strategic decision-making. Beyond technical execution, you will collaborate with business stakeholders to translate operational needs into technical requirements and spearhead initiatives to improve overall system efficiency. In this role, you will: - Partner across engineering organizations to spearhead and execute high-impact, company-wide initiatives, - Mentor and upskill junior engineers, fostering a culture of technical excellence and continuous growth. - Collaborate with leadership, product engineers, program managers, and data scientists to deeply understand and prioritize business data requirements. - Leverage deep technical expertise to design and architect scalable, high-performance data solutions. - Develop, launch, and optimize highly efficient, reliable ELT/ETL pipelines capable of processing both large-scale and specialized datasets. - Intelligently design robust data models optimized for high-speed storage, accessibility, and downstream retrieval. - Implement and deploy rigorous data quality frameworks to guarantee data accuracy, freshness, and trust. - Maintain full technical ownership of the end-to-end data engineering lifecycle for your team's solutions. - Participate in the team's on-call rotation to ensure platform stability and support operational health. - Partner with software engineering teams to design and build next-generation data systems that enable rapid, self-service data consumption. - A BE in Computer Science or equivalent with 6+ years of professional experience as a Data Engineer or in a similar role - Experience building scalable data pipelines in Spark using Airflow scheduler/executor framework or similar scheduling tools. - Experience with Databricks and its APIs. - Experience with modern databases (Redshift, Dynamo DB, Mongo DB, Postgres or similar) and data lakes. - Proficient in one or more programming languages such as Python/Scala and rock-solid SQL skills. - Champion automated builds and deployments using CICD tools like Bitbucket, Git - Experience working with large-scale, high-performance data processing systems (batch and streaming) - Experience working for SAAS companies - Experience with Machine Learning - Committed code to open source projects - Experience building self-service tooling and platforms Benefits & Perks Atlassian offers a wide range of perks and benefits designed to support you, your family and to help you engage with your local community. Our offerings include health and wellbeing resources, paid volunteer days, and so much more. To learn more, visit go.atlassian.com/perksandbenefits . About Atlassian At Atlassian, we're motivated by a common goal: to unleash the potential of every team. Our software products help teams all over the planet and our solutions are designed for all types of work. Team collaboration through our tools makes what may be impossible alone, possible together. We believe that the unique contributions of all Atlassians create our success. To ensure that our products and culture continue to incorporate everyone's perspectives and experience, we never discriminate based on race, religion, national origin, gender identity or expression, sexual orientation, age, or marital, veteran, or disability status. All your information will be kept confidential according to EEO guidelines. To provide you the best experience, we can support with accommodations or adjustments at any stage of the recruitment process. Simply inform our Recruitment team during your conversation with them. To learn more about our culture and hiring process, visit go.atlassian.com/crh .

Role Description We are seeking an experienced Senior Data Engineer / Data Platform Engineer to join a high-impact SME Fraud Data Warehouse (DWH) programme. This is a pivotal role where you will design, build, migrate, and optimise a large-scale analytical platform on Teradata Vantage as a Service (VaaS) with an AWS-based data lake. You will work alongside a talented cross-functional team to deliver a robust fraud analytics platform that drives real business outcomes. Qualifications - Strong hands-on experience with Teradata Vantage as a Service (VaaS) - Proven expertise in AWS-based data lake architectures — including S3, Glue, Redshift, and Athena - Experience designing and building large-scale analytical platforms - Solid understanding of data migration strategies and best practices - Strong SQL and data modelling skills Requirements - Design and architect analytical data solutions on Teradata VaaS and AWS - Build, migrate, and optimise large-scale data pipelines and data warehouse structures - Collaborate with data architects, analysts, and fraud SMEs to translate business requirements into technical solutions - Ensure data quality, performance, and reliability across the platform - Contribute to best practices in data modelling, pipeline development, and platform governance Company Description

Role Description We are looking for a skilled Data Engineer with solid hands-on experience in PySpark, AWS Glue, and ETL development to build and maintain scalable, production-grade data pipelines on AWS. You will be part of a delivery-focused team working on complex data engineering challenges, contributing to data lake architecture and end-to-end pipeline development. Qualifications - Strong hands-on experience with PySpark and AWS Glue - Proven track record in ETL pipeline development and optimisation - Experience orchestrating workflows with AWS Step Functions - Proficiency in serverless development using AWS Lambda (Python) - Good SQL skills and a solid understanding of data processing principles Requirements - Design, develop, and maintain scalable ETL pipelines using PySpark and AWS Glue - Build and optimise data ingestion, transformation, and loading workflows - Orchestrate data workflows using AWS Step Functions - Develop serverless functions using AWS Lambda (Python) - Work with data lake architectures on AWS to support analytical use cases - Ensure pipeline reliability, monitoring, and performance optimisation Company Description