4 Data Analysts Jobs

ETL Process Design: Designing and developing ETL processes using Talend for data integration and transformation. Data Extraction: Extracting data from various sources, including databases, APIs, and flat files. Data Transformation: Transforming data to meet business requirements and ensuring data quality. Data Loading: Loading transformed data into target systems, such as data warehouses or data lakes. Job Scheduling: Scheduling and automating ETL jobs using Talend's scheduling tools. Performance Optimization: Optimizing ETL workflows for efficiency and performance. Error Handling: Implementing robust error handling and logging mechanisms in ETL processes. Data Profiling: Performing data profiling to identify data quality issues and inconsistencies. Documentation: Documenting ETL processes, data flow diagrams, and technical specifications. Collaboration with Data Teams: Working closely with data analysts, data scientists, and other stakeholders to understand data requirements. Min 4 to Max 7yrs of Relevant exp. Locations : Mumbai, Delhi NCR, Bengaluru , Kolkata, Chennai, Hyderabad, Ahmedabad, Pune, Remote

What will your day look like? - Leading a dynamic team to deliver high impact risk solutions across credit risk (underwriting, exposure controls and line management). - Work with stakeholders across product management, data science, and engineering to build relationship with the partner teams and drive implementation of risk strategies - Manage challenging time constraints to ensure on-time delivery of projects. - Work closely with partner teams in identifying, evaluating, and recommending new data that helps in risk differentiation. - Analyze loss trends and simulate risk decisioning strategies that help optimize revenue, approval rates etc. - Work closely with data science team and recommends credit risk decisioning and model deployment strategy. - Build a risk scorecard that leverages both internal performance data and external performance data that will be leveraged for credit decisioning at both underwriting and account management reviews for existing customers. - Collates analysis and builds presentations that helps articulate the risk strategy for the leadership team. To Help Us Level Up, You Will Ideally Have : - Quantitative background in engineering, statistics, math, economics, business, or related disciplines. - 5+ years experience in analyzing data and using database query language (e. SQL) analysis and programming and developer tools such as Python, R, data bricks in a finance or analytics field. - 2+ years of experience in leading high performing team of analysts. - Experience in working with non-traditional data such as social media will be a big plus. - Prior model building experience is a plus but not critical. - Possesses an analytical mindset and strong problem-solving skills. - Attention to detail and ability to multitask. - Comfortable working in a fast-paced environment and dealing with ambiguity. - Possesses strong communication, interpersonal and presentation skills; and ability to engage and collaborate with multiple stakeholders across teams. - Extremely proactive communicator willing to raise flags when needed and keep team members informed of ongoing risk or fraud related activities.

What kind of person are we looking for We are seeking a highly skilled and motivated Business Intelligence Assistant Manager to join us. The successful candidate will be responsible for overseeing data analysis, developing insights, and supporting business strategies through data-driven decision making. This role requires a strong background in BI analytics, excellent people managerial skills, and a deep understanding of fintech industry trends. What would you get if you worked with us You'll be closely working on problem statements and influencing decisions that impact 42 million merchants. While supporting merchant experience strategy & operations, youll own data visibility, dashboarding, insights & subsequent strategic decision making. By creating powerful narratives based on support data & ticket insights, youll help the merchant experience strategy & operations team to prioritize & achieve ambitious goals. What would you get to do in this role Be an integral part of the Merchant experience strategy team and define the critical metrics to understand MX performance. Monitor performance trends and do data analysis for any interventions done to improve merchant experience. Collaborate closely with the internal to merchant experience teams like process design, Product operations, operations, Automation, etc. to highlight problems/inefficiencies identified by right analytical problem statements. Own the entire insight generation and build narratives by working on deep, thorough analysis to provide unbiased answers on the identified problem statement. Also, come up with unidentified / unknown problem statements based on new data insights. These insights and decisions will be influenced based on your presentation of the evidence, backed by data-driven hypothesis Identify & help stakeholders prioritize improvement opportunities by co-owning experience & business metrics. Move past just being the "Data person" and contribute with individual thoughts on how to improve the critical merchant experience metrics.. Act like a business owner & leverage data to influence stakeholder decisions. Work with central analytics team to ensure that the dashboards are designed and built in a way that makes it easy for the teams to consume the data they need What do you need to have to apply for this position Minimum 3-5 years of analytics experience in relevant roles. Lead and mentor a team of data analysts, ensuring high performance and continuous development. Ability to manage multiple projects/BUs and priorities simultaneously. Present findings and insights to senior management and other stakeholders in a clear and concise manner. Collaborate with business units to understand their needs and provide data-driven recommendations to support strategic initiatives. Strong problem solving & analytical skills, followed by strong stakeholder management skills. Identify opportunities for process improvement and implement best practices in data analysis and reporting. Penchant for business & curiosity to understand how the product works Ability to clearly explain thoughts and ideas either verbally or in the written form. Candidates who are able to explain the story behind their analysis will find themselves at an advantage. Intuition for data and ability to handle big data sources. Strong working knowledge in Excel and visualization tools like PowerBI, Tableau, Qlik Sense. Ability to write complex queries on SQL to manipulate, consolidate multiple data sources for the purpose of dashboarding and analysis, is a pulse. Understanding of data-analysis languages such as R, Python and in core statistical concepts is good to have.

Responsibilities: Design, develop, and maintain scalable data pipelines using Python and AWS Redshift Optimize and tune Redshift queries, schemas, and performance for large-scale datasets Implement ETL/ELT processes to ensure accurate and timely data availability Collaborate with data analysts, engineers, and product teams to understand data requirements Ensure data quality, consistency, and integrity across systems Automate data workflows and improve pipeline efficiency using scripting and orchestration tools Monitor data pipeline performance and troubleshoot issues proactively Maintain documentation for data models, pipelines, and system configurations Ensure compliance with data governance and security standards