Data Engineer
- Collaborating with cross-functional teams to understand data requirements, and design efficient, scalable, and reliable ETL processes using Python and Databricks
- Developing and deploying ETL jobs that extract data from various sources, transforming them to meet business needs.
- Taking ownership of the end-to-end engineering lifecycle, including data extraction, cleansing, transformation, and loading, ensuring accuracy and consistency.
- Creating and managing data pipelines, ensuring proper error handling, monitoring and performance optimizations
- Working in an agile environment, participating in sprint planning, daily stand-ups, and retrospectives.
- Conducting code reviews, providing constructive feedback, and enforcing coding standards to maintain a high quality.
- Developing and maintaining tooling and automation scripts to streamline repetitive tasks.
- Implementing unit, integration, and other testing methodologies to ensure the reliability of the ETL processes
- Utilizing REST APIs and other integration techniques to connect various data sources
- Maintaining documentation, including data flow diagrams, technical specifications, and processes.
- Designing and implementing tailored data solutions to meet customer needs and use cases, spanning from streaming to data lakes, analytics, and beyond within a dynamically evolving technical stack.
- Collaborate seamlessly across diverse technical stacks, including Databricks, Snowflake, etc.
- Developing various components in Python as part of a unified data pipeline framework.
- Contributing towards the establishment of best practices for the optimal and efficient usage of data across various on-prem and cloud platforms.
- Assisting with the testing and deployment of our data pipeline framework utilizing standard testing frameworks and CI/CD tooling.
- Monitoring the performance of queries and data loads and perform tuning as necessary.
- Providing assistance and guidance during QA & UAT phases to quickly confirm the validity of potential issues and to determine the root cause and best resolution of verified issues.
- Adhere to Agile practices throughout the solution development process.
- Design, build, and deploy databases and data stores to support organizational requirements. 4+ years of experience developing data pipelines and data warehousing solutions using Python and libraries such as Pandas, NumPy, PySpark, etc.
- 3+ years hands-on experience with cloud services, especially Databricks, for building and managing scalable data pipelines
- 3+ years of proficiency in working with Snowflake or similar cloud-based data warehousing solutions
- 3+ years of experience in data development and solutions in highly complex data environments with large data volumes.
- Solid understanding of ETL principles, data modelling, data warehousing concepts, and data integration best practices
- Familiarity with agile methodologies and the ability to work collaboratively in a fast-paced, dynamic environment.
- Experience with code versioning tools (e.g., Git)
- Knowledge of Linux operating systems
- Familiarity with REST APIs and integration techniques
- Familiarity with data visualization tools and libraries (e.g. Power BI)
- Background in database administration or performance tuning
- Familiarity with data orchestration tools, such as Apache Airflow
- Previous exposure to big data technologies (e.g. Hadoop, Spark) for large data processing
- Strong analytical skills, including a thorough understanding of how to interpret customer business requirements and translate them into technical designs and solutions.
- Strong communication skills both verbal and written. Capable of collaborating effectively across a variety of IT and Business groups, across regions, roles and able to interact effectively with all levels.
- Self-starter. Proven ability to manage multiple, concurrent projects with minimal supervision. Can manage a complex ever changing priority list and resolve conflicts to competing priorities.
- Strong problem-solving skills. Ability to identify where focus is needed and bring clarity to business objectives, requirements, and priorities. Preferred Qualifications
- Experience in financial services
- Knowledge of regulatory requirements in the financial industry Education: Bachelor's degree in Computer Science, Engineering, or a related field (or equivalent experience). NTT DATA is seeking a highly skilled Data Engineer with over 4+ years of experience to join our team to help a strategic banking client in various data transformation activities., NTT DATA is a $30 billion trusted global innovator of business and technology services. We serve 75% of the Fortune Global 100 and are committed to helping clients innovate, optimize and transform for long term success. As a Global Top Employer, we have diverse experts in more than 50 countries and a robust partner ecosystem of established and start-up companies. Our services include business and technology consulting, data and artificial intelligence, industry solutions, as well as the development, implementation and management of applications, infrastructure and connectivity. We are one of the leading providers of digital and AI infrastructure in the world. NTT DATA is a part of NTT Group, which invests over $3.6 billion each year in R&D to help organizations and society move confidently and sustainably into the digital future. Visit us at us.nttdata.com Our people are the most critical component of our long-term success and their health and wellbeing are our priority. You will enjoy a comprehensive, locally competitive benefits package.
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