We are seeking a highly analytical and detail-oriented Senior Data Analyst to join our growing team. In this role, you will work closely with cross-functional teams to uncover insights, optimize business performance, and contribute to strategic decision-making through data-driven approaches. Responsibilities Perform deep-dive analysis using statistical methods to extract meaningful insights and guide business decisions. Design and build dashboards, reports, and visualizations using tools like Tableau, Power BI, or similar platforms to communicate insights clearly to stakeholders. Develop robust data models to support forecasting, trend analysis, and predictive analytics. Maintain high data integrity by conducting regular data quality checks and resolving anomalies or inconsistencies. Collaborate with teams such as Marketing, Finance, and Product to understand data requirements and provide analytical solutions that support their objectives. Identify and implement automation solutions for recurring reports and processes to improve efficiency and scalability. Qualifications Bachelor's or Master's degree in Statistics or Applied Mathematics or equivalent experience Minimum of 3 years in a data analysis role, with demonstrated success in solving business problems through data. Solid knowledge of statistical techniques such as regression, clustering, and hypothesis testing. Visualization Tools: Proficiency in tools like Tableau, Power BI, or equivalent. Advanced skills in SQL, with hands-on experience in Python or R for data wrangling and analysis. Proven experience in managing and improving data quality, including cleansing and validation. Capable of managing multiple priorities and projects efficiently. Show more Show less

We are seeking a seasoned Lead Data Insights Analyst to join our data team and contribute to high-impact analytics initiatives across business units. The ideal candidate brings extensive experience analyzing financial and business data in professional services, and a proven record of leading analytical teams and projects Responsibilities Architect and lead the execution of analytics projects that drive business decision-making. Take ownership of KPI development, monitoring, and enhancement aligned with strategic goals. Design and refine scalable data models and pipelines for analysis and reporting. Apply statistical and machine learning methods to extract insights from diverse datasets. Deliver clear and interactive visual reports to stakeholders using modern BI tools. Collaborate with product, engineering, and business teams to define and meet data needs. Implement data quality checks and ensure compliance with governance practices. Provide coaching and guidance to junior data team members. Engage in Agile ceremonies including daily stand-ups, retrospectives, and planning sessions. Promote modular, scalable data solutions with long-term maintainability in mind. Lead peer reviews of analytical code and drive continuous process optimization. Qualifications Minimum 5 years of professional experience in data analytics, preferably in financial and business domains. 3+ years in a leadership capacity, managing projects and mentoring team members. Bachelor's degree in a relevant field such as Data Science, Statistics, Engineering, or Business. Strong command of SQL and at least one of Python, R, or equivalent scripting language. High proficiency in data visualization using platforms such as Tableau, Power BI, or Looker. Solid grasp of data modeling, ETL pipelines, and data warehousing architectures. Experience working in Agile or Kanban settings with active participation in sprints, code reviews, and iterative delivery models. Expertise in statistical evaluation, A/B testing, forecasting, and basic machine learning methods. Ability to gather business requirements and deliver technical solutions aligned with organizational goal Familiarity with performance metrics in tech-focused environments and understanding of key influencing factors. Show more Show less

We are looking for a highly skilled Senior Data Engineer to join our team and help design, build, and optimize scalable data pipelines and infrastructure. You’ll work closely with data scientists, analysts, and engineering teams to ensure reliable data delivery, support advanced analytics, and contribute to our data-driven decision-making. Responsibilities Responsible for developing and supporting data pipelines that support and enable the overall strategy of expanded data initiatives, optimized services, and advanced analytics. Design and implement scalable data warehouse architectures, including building ETL pipelines across Big Data ecosystems (cloud, on-premises, hybrid). Facilitate data discovery workshops with business units, product managers, analysts, and technical stakeholders to gather requirements. Ensure testing frameworks and data monitoring are in place for dependable, trusted datasets. Collaborate with business SMEs, analysts, solution architects, and engineering teams to align data design with business strategies. Define and document best practices, coding standards, and architectural frameworks. Assist BI engineers in resolving complex technical issues. - Participate in an on-call rotation ensuring the health of data systems. Qualifications Bachelor's or Master's in Computer Science, Information Systems, or a related field. Over 3 years of experience in data architecture including modeling, integration, and analytics. 5+ years of expertise in custom ETL development and maintenance. Proficient in programming languages such as Python and OOP. - Strong hands-on experience with SQL and relational database structures. Proficient with cloud platforms like AWS or Google Cloud. - Experience with CI/CD pipelines and version control (GitHub, GitLab). Skilled with relational databases such as Snowflake and Redshift. Solid understanding of orchestration tools (preferably Airflow), file systems (AWS S3, GCS), data partitioning, and real-time processing. Exposure to real-time event streaming platforms such as Kafka or Kinesis will be an added Advantage Show more Show less

About the Role We’re looking for a Lead Data Engineer to join our growing Data & Analytics team. You’ll play a critical role in designing, building, and optimizing the infrastructure that powers our data products and insights. This is a hands-on leadership role where you’ll drive technical direction, mentor team members, and ensure the reliability and scalability of our data systems. What you will do Lead the design and development of robust, scalable, and secure data pipelines and workflows. Own and evolve our data architecture, ensuring it supports current and future business needs. Collaborate cross-functionally with data analysts, data scientists, and business stakeholders to understand requirements and deliver data solutions. Manage and enhance data ingestion and transformation processes using tools like Fivetran, Airflow, and Python. Oversee data warehouse design and optimization using Snowflake and AWS services. Promote best practices in data modeling, ETL/ELT design, and data governance. Enable efficient and consistent reporting by ensuring well-structured datasets for Tableau and other BI tools. Mentor junior engineers and foster a culture of technical excellence and continuous learning. Tech Stack You’ll Work With Languages & Tools: Python, SQL Data Orchestration: Apache Airflow Data Integration: Fivetran Data Warehousing: Snowflake BI & Visualization: Tableau Cloud Platform: AWS (e.g., S3, Lambda, EC2, etc.) Version Control & CI/CD: Git, GitHub Actions What We’re Looking For 7+ years of experience in data engineering, with at least 1–2 years in a technical leadership role. Strong knowledge of modern data architectures, including ELT pipelines, data lakes, and warehousing. Proficiency in Python and SQL; experience building data pipelines and automations. Deep experience with Snowflake or similar cloud-based data warehouses. Experience with cloud platforms like AWS, Google Cloud, or Azure and best practices. Proven experience with Airflow or similar orchestration tools. Understanding of data modeling techniques and performance optimization strategies. Strong communication and collaboration skills, with the ability to explain complex data topics to non-technical stakeholders. Preferred Qualifications Exposure to Kafka or other streaming data platforms. Familiarity with data privacy, compliance, and governance frameworks. Experience collaborating with data science teams and understanding machine learning workflows. Experience with data visualization tools (e.g., Tableau, Power BI) to communicate insights effectively. Why Join Us As a Lead Data Engineer with us, you'll engage in solving some of the most compelling and complex problems in the data engineering landscape, including: Handling Unstructured Data: Develop scalable solutions to process and analyze unstructured data from various sources, enabling meaningful insights from complex datasets. Optimizing Real-Time Data Processing: Design and implement low-latency data pipelines using tools like Apache Kafka and Apache Flink to support real-time applications in domains such as autonomous vehicles and smart grids. Ensuring Data Integrity and Lineage: Establish comprehensive data lineage systems to track data origins, transformations, and movements, facilitating error detection and compliance auditing. Scalability and Performance Optimization: Address challenges related to processing large datasets, optimizing query performance, and ensuring efficient data storage and retrieval in cloud environments. Show more Show less