Job Title Data Analyst
Location Jaipur, Rajasthan.
Job Type Full-Time
About Us
At Paysecure, we harness the power of data analytics to redefine financial services. Our team is dedicated to delivering cutting-edge data-driven solutions that transform customer experiences and streamline operations.
We are looking for passionate Data Analyst with 3-7 years of experience to join our dynamic team and drive innovation in this rapidly evolving sector.
Responsibilities:
Data Ingestion and Integration:
Youll be working with handling various data formats and protocols, ensuring reliable, real-time data integration and enabling a consistent, structured data pipeline.
Data Modeling:
You will architect and implement robust data models that organize information logically and intuitively.
ETL (Extract, Transform, and Load) Development:
You’ll oversee the ETL pipeline, transforming raw data into a polished format that’s ready for analysis. This process includes managing data extraction from multiple sources, converting it to a standard format, and loading it into optimized storage solutions for rapid querying and reporting.
Data Quality and Validation:
You’ll implement rigorous quality control practices to validate, clean, and standardize data. This includes designing and executing quality checks, resolving discrepancies, error correction methods and establishing practices that ensure consistent, reliable data for downstream applications.
Cross-Functional Collaboration:
Your role involves working closely with product managers, data scientists, software engineers and business stakeholders to support their data needs. This includes delivering clean, structured data, supporting model implementation, and aligning on data strategies that enhance insights and decision-making across the organization.
System Monitoring and Issue Resolution:
You’ll proactively monitor data systems, identifying and resolving any data-related issues swiftly to maintain seamless operations.
Comprehensive Documentation:
Your role includes creating clear, thorough documentation of processes, configurations, and system details.
Desired Skills & Qualifications:
Programming Proficiency:
Strong programming skills, particularly in Python, Java, or Scala, with a focus on data processing and automation.
Database Management and SQL Expertise:
Advanced knowledge of SQL for database querying, manipulation, and performance tuning; experience with both relational (e.g., PostgreSQL, MySQL) and NoSQL (e.g., MongoDB, Cassandra) databases.
Data Warehousing and ETL Experience:
Hands-on experience with data warehousing tools and platforms (e.g., Amazon Redshift, Snowflake, Google BigQuery) and ETL tools (e.g., Apache NiFi, Talend, Informatica).
Big Data Tools and Technologies:
Familiarity with big data frameworks like Apache Hadoop, Spark, and Kafka for handling and processing large volumes of data.
Cloud Platform Knowledge:
Experience with one or more of the cloud data solutions (e.g., AWS, GCP, Azure) including storage, compute, and data pipeline services such as AWS Glue, Azure Data Factory, and Google Cloud Dataflow.
Data Modeling and Schema Design:
Proficiency in designing efficient, scalable data models and defining schemas that support data consistency and performance.
Data Quality Management:
Familiarity with data validation, cleansing, and quality assurance practices to ensure data accuracy and reliability.
Automation and Scripting:
Skills in automation, with experience in scripting for process automation (e.g., using Python or Shell scripting) to streamline data workflows.
Version Control and DevOps Practices:
Knowledge of version control (e.g., Git) and DevOps principles, including CI/CD pipelines for deploying and maintaining data infrastructure.
Industry Experience in Ecommerce, Banking, Payments, or Insurance (preferred):
Previous experience working within banking, finance, or insurance sectors, with an understanding of industry-specific data requirements, regulatory standards, and compliance practices (e.g., GDPR, PCI DSS).
Data Governance and Security (preferred):
Familiarity with data governance practices and security protocols unique to financial and insurance industries, ensuring data privacy, compliance, and protection of sensitive information.
Financial Data Analytics (preferred):
Experience with financial data structures, transaction data, and knowledge of key performance indicators (KPIs) relevant to banking and insurance.
Educational Background:
A Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, or a related technical field.
Relevant Experience:
5+ years of professional experience in data engineering or related roles, ideally within fast-paced, data-driven environments in banking, financial services, or insurance domain.
What We Offer:
- Opportunity to work on a fast growing international business with impactful projects that directly shape the future of payments and fintech.
- A collaborative and innovative work environment that encourages learning and growth.
- Competitive salary, benefits, and the chance to work with cutting-edge technologies in a rapidly growing industry.
