This role is for one of Weekday’s clients

Min Experience: 5+ years
Location: Bengaluru, Karnataka, India
JobType: full-time

We are seeking an experienced and technically strong Data Engineer & Analytics Officer with 5–12 years of professional experience to design, build, and maintain scalable data solutions that support advanced analytics, reporting, and data-driven decision-making. The ideal candidate will have strong hands-on expertise in Python and KDB+, with a solid understanding of data engineering, time-series data, analytics platforms, and high-performance data processing.

You will work closely with technology, analytics, product, and business teams to develop reliable data pipelines, optimize data systems, and transform complex datasets into meaningful insights. This role is well suited for someone who enjoys working with large-scale datasets, solving complex technical problems, and building efficient data infrastructure.

Requirements

Key Responsibilities

• Design, develop, and maintain robust data pipelines and ETL/ELT workflows for ingesting, processing, transforming, and delivering structured and unstructured data.
• Develop high-performance data solutions using Python and KDB+, ensuring scalability, reliability, and efficiency.
• Work extensively with KDB+/q for time-series data processing, analytics, querying, and storage.
• Build and optimize data models and datasets to support analytical applications, dashboards, reporting, and business intelligence.
• Develop Python-based services, automation scripts, data-processing frameworks, and analytical tools.
• Perform data profiling, validation, cleansing, reconciliation, and quality checks to ensure accuracy and consistency.
• Optimize queries, pipelines, and data-processing workflows to improve performance and reduce processing time.
• Work with large and complex datasets, identifying patterns, anomalies, trends, and opportunities for process improvement.
• Collaborate with analysts, engineers, product managers, and business stakeholders to understand data requirements and translate them into scalable technical solutions.
• Troubleshoot data pipeline failures, system issues, and data-quality problems and implement long-term solutions.
• Establish best practices around data governance, documentation, monitoring, testing, and security.
• Contribute to the development of analytical frameworks and reporting solutions that enable data-driven decision-making.

Must-Have Skills

• 5–12 years of professional experience in data engineering, analytics engineering, quantitative development, or a related field.
• Strong programming expertise in Python, including data processing, automation, API integration, and analytical applications.
• Hands-on experience with KDB+ and q, particularly for time-series data management and high-performance analytics.
• Strong understanding of data structures, databases, SQL, ETL/ELT processes, and data modeling.
• Experience working with large-scale datasets and performance-sensitive data-processing environments.
• Strong analytical and problem-solving skills with the ability to investigate complex data issues.
• Experience building reliable, maintainable, and production-grade data pipelines.
• Good understanding of data quality, validation, monitoring, and reconciliation practices.

Good-to-Have Skills

• Experience in financial markets, trading, investment banking, or quantitative analytics.
• Exposure to market data, tick data, or other high-frequency/time-series datasets.
• Familiarity with cloud platforms such as AWS, Azure, or GCP.
• Knowledge of Kafka, Spark, Airflow, or other modern data engineering technologies.
• Experience with CI/CD, Git, Docker, and production monitoring tools.
• Strong understanding of distributed systems and scalable data architectures.