Tarandeep Singh
Manager Data & Analytics Engineering
KENNESAW,GA
Summary
Innovative and results-oriented professional with over 12 years of experience transforming data into a strategic asset, complemented by a proven track record in leading teams across diverse domains, including Data Engineering, Business Intelligence, Analytics, and Product Management. Expertise in blending technology skills with extensive Agile and Scrum methodologies to refine product strategies and enhance Analytics and Data Ecosystems. Energetic presenter and confident communicator adept at conveying information clearly and efficiently, ensuring benefits for end users. Creative problem-solver focused on identifying solutions and optimizing the use of organizational data for maximum impact.
Overview
12
12
years of professional experience
7
7
Certifications
1
1
Language
Work History
Manager Data & Analytics Engineering(Product)
Prizpeiks
11.2022 - Current
- Strategic Leadership: Define and execute the enterprise vision for Data, Analytics, BI, and Data Products, ensuring alignment with business strategy, growth priorities, and long-term organizational objectives.
- Executive Partnership: Collaborate with C-level and senior leadership to shape, fund, and prioritize high-impact data and analytics initiatives, embedding data-driven decision-making across the business.
- BI, Analytics & Data Product Strategy: Lead the design and execution of BI and data product strategies, establishing clear roadmaps, managing priorities, and delivering actionable insights that drive revenue growth, operational efficiency, and customer engagement.
- Data Product Ownership: Oversee the end-to-end lifecycle of enterprise data products—defining product vision, roadmaps, KPIs, and backlog management—while ensuring data products deliver measurable business value and user adoption.
- Platform & Infrastructure Leadership: Direct the architecture, scalability, and governance of modern cloud-based platforms (e.g., BQ, dbt, GKE, Data Proc, Hevo, Tableau, Streamlit), ensuring secure, efficient, and future-ready infrastructure.
- Pipeline & Integration Excellence: Lead the design and optimization of batch, real-time, and streaming pipelines, enabling seamless data integration, accessibility, and high-performance analytics across the enterprise.
- Team Leadership & Development: Manage and grow a high-performing team of 10+ data engineers, BI developers, and product-focused analytics professionals; provide mentorship, career development, and foster a culture of innovation.
- Analytics & BI Enablement: Drive the delivery of enterprise BI and analytics solutions (Tableau, DBT, Submittal, etc.), building dashboards, visualizations, and data stories that empower faster and smarter decision-making.
- Cross-Functional Collaboration: Partner with Product, Data Science, Finance, Marketing, and Operations teams to design and deliver data products and analytics solutions that address key business needs and create new growth opportunities.
- Data Governance & Compliance: Establish and enforce governance, security, and quality frameworks using dbt, IAM policies, and monitoring tools (DataDog, Grafana, Slack, incident.io), ensuring trust, compliance, and reliability.
- Innovation & Continuous Improvement: Champion automation, advanced analytics, and AI/ML-powered data products to modernize reporting, enhance customer experiences, and improve scalability.
- Stakeholder Engagement: Act as the executive liaison for analytics and data product initiatives, ensuring adoption, alignment, and demonstrable value for internal and external stakeholders.
- Financial Stewardship: Manage the BI, Data Products & Engineering budget, ensuring cost-effective use of resources and maximizing ROI from data platforms and tools.
- Enterprise Impact: Lead the execution of enterprise-wide BI, data product, and reporting strategies to strengthen decision-making, accelerate digital transformation, and drive profitability.
Manager Data Analytics(Product)
Relay Payments
06.2022 - 11.2022
- Executive Leadership: Report to the CTO and lead an agile BI and Data Engineering team to meet the organization’s growing demand for business intelligence, analytics, and data-driven decision-making.
- Strategy & Vision: Define and execute the BI and data strategy, including organizational design, governance, and technical architecture, ensuring alignment with enterprise priorities and long-term business goals.
- Data Product Ownership: Establish the vision, strategy, and roadmap for data products and analytical capabilities, enabling business units with scalable, high-value solutions that drive measurable impact.
- Program & Delivery Management: Guide project and sprint planning, ensuring readiness by refining user stories, features, and priorities to balance short-term deliverables with long-term strategic initiatives.
- Stakeholder Collaboration: Partner with business leaders to understand challenges, gather requirements, and translate needs into analytical solutions that inform strategy, improve decision-making, and unlock growth opportunities.
- BI & Dashboard Development: Oversee the design, implementation, and maintenance of internal and external dashboards, delivering actionable insights through advanced visualizations and data storytelling.
- Advanced Analytics Enablement: Drive adoption of descriptive, predictive, and prescriptive analytics, enabling stakeholders to anticipate trends, optimize operations, and improve performance outcomes.
- Roadmap & Requirements Management: Formulate business and technical requirements, create product roadmaps, and deliver advanced data solutions with clear business value.
- Modernization & Tooling: Spearheaded the adoption of dbt for defining and deploying reusable data models, improving efficiency, standardization, and documentation across the enterprise data model (EDM).
- Enterprise Data Modeling: Transitioned reporting structures from Looker views to dbt-based data models, streamlining analytics workflows and enhancing data governance.
Lead Data Engineer
Chick Fil-A
09.2015 - 08.2020
- Design, implement, and optimize enterprise data pipelines, including ingestion, transformation, storage, and high-throughput processing for large-scale analytics using Redshift, Databricks, and AWS services (Glue, S3, etc.).
- Develop and maintain data models, data structures, and warehouse schemas leveraging dbt and Redshift, ensuring scalable and efficient analytics solutions.
- Build, configure, and maintain environments, processes, and tools to improve the lifecycle of data lake implementations, prototypes, and production-ready analytics solutions.
- Implement and optimize end-to-end data lifecycle frameworks, including data acquisition, migration, transformation, preparation, and consumption for enterprise-wide analytics use cases.
- Evaluate, integrate, and adopt modern data technologies and analytics tools (Databricks, dbt, Redshift, Monte Carlo, Tableau, Glue) to enhance performance, scalability, and reliability of the data ecosystem.
- Develop and implement automated data monitoring, validation, and governance processes using Monte Carlo and other tooling to ensure data quality, consistency, and compliance.
- Collaborate with cross-functional teams (Product, Analytics, Engineering) to translate business requirements into technical solutions and actionable insights, delivering visualizations and dashboards via Tableau.
- Stay current with emerging technologies, cloud services, and best practices in computation, data curation, and visualization to guide architecture and implementation decisions.
- Build reusable frameworks and pipelines to accelerate analytics delivery across different data maturity levels, supporting both operational and advanced analytics teams.
- Drive technical initiatives that enable trusted, high-performance data products and facilitate a strong enterprise data culture.
- Translate and prioritize business and technical requirements into actionable tasks for engineering teams, ensuring alignment across Data Development, Data Support, Data Platforms, and Data Governance.
- Collaborate within agile frameworks, working closely with Product Owners, Scrum Masters, Developers, and Test Engineers to manage backlog, sprints, and delivery tooling effectively.
- Define and promote the vision of treating data as both a strategic asset and a product, driving adoption, commercial value, and operational viability.
- Evaluate and integrate modern data technologies (e.g., Snowflake, dbt, Ascend, Databricks, Delta Lake) to enhance the organization’s Data & Analytics ecosystem.
- Build, configure, and maintain environments, processes, and tools to support all stages of data lake and analytics solution development, including proof-of-concepts, prototypes, and production-ready pipelines.
- Drive enterprise analytics strategy, fostering a strong data culture through the delivery of reliable, trusted data products and simplified, user-friendly analytics experiences.
SENIOR DATA ANALYST
COX ENTERPRISES-MANHEIM
09.2015 - 08.2020
- Partner with Business Project Owners and Senior Management to lead all aspects of data product delivery, ensuring alignment with strategic objectives.
- Translate business requirements into scalable, analytics-ready solutions by designing, developing, and implementing ETL workflows and advanced analytical architectures.
- Identify, recommend, and implement process improvements to enhance data platform efficiency and data quality, using tools such as Alteryx Designer and Alteryx Server.
- Design, develop, and maintain end-to-end data pipelines and workflows using Alteryx and Informatica, enabling seamless data ingestion, transformation, and integration across multiple source systems.
- Perform data analysis, profiling, and validation to ensure high-quality, reliable data for reporting and analytics purposes.
- Support ETL monitoring, troubleshooting, and issue resolution, ensuring timely delivery of data products and analytics outputs
- Develop and document technical specifications for ETL workflows supporting Tableau dashboards, ensuring accurate and actionable business insights.
- Contribute to all phases of the SDLC, including planning, analysis, design, development, testing, implementation, and maintenance, delivering timely results under tight deadlines.
- Provide technical expertise in BI and middleware services, guiding problem resolution and driving analytics innovation to increase business value.
- Work with large datasets, collaborating with Machine Learning engineers to apply algorithms, build predictive models, and generate data-driven insights.
- Define data requirements, validate data quality, perform data cleansing and profiling, and identify inconsistencies using SQL queries and Alteryx ETL workflows.
- Lead multiple analytics projects concurrently, independently designing innovative methods to measure program effectiveness and optimize decision-making.
- Translate data from source systems (SQL databases, Informatica workflows, CSV/DAT files) into analytics-ready datasets and workflows using Alteryx.
- Build, publish, and schedule ETL and data validation workflows in Alteryx, leveraging features such as data investigation, parsing, transforms, interfaces, and developer tools.
- Design and develop interactive Tableau dashboards, integrating multiple data sources, custom queries, and data blending, using action filters, calculated fields, parameters, hierarchies, groups, and sets.
- Publish and schedule dashboards via Tableau Server, ensuring accessibility and usability for business stakeholders.
- Participate actively in Agile Scrum processes, managing analytics projects from inception through deployment using tools such as Jira, Rally, VersionOne, Mingle, and Kanban.
SQL SERVER DEVELOPER
TRAVEL INCORPORATED
04.2015 - 08.2015
- Designed, developed, and implemented complex stored procedures, triggers, functions, indexes, tables, views, and T-SQL code following industry-standard SQL coding practices.
- Developed and maintained ETL pipelines for business data consumption, leveraging existing patterns and building scalable, reusable solutions for project execution.
- Ensured data quality and consistency by filtering invalid or duplicate data using advanced T-SQL queries and implementing constraints, triggers, and validation rules.
- Optimized query performance through T-SQL refinements, eliminating redundant columns, reducing unnecessary computations, and improving overall database efficiency.
- Developed complex T-SQL scripts to support application conversions, data migrations, and transformations.
- Coordinated and executed database migrations from SQL Server 2005 to SQL Server 2012, ensuring seamless transition and minimal downtime.
- Managed Type-1 and Type-2 Slowly Changing Dimensions (SCD) procedures within a Data Warehouse environment (Kimball methodology).
- Designed and implemented SSIS packages in BIDS to load, transform, and validate data for the Data Warehouse, ensuring reliable and accurate analytics reporting.
SENIOR BUSINESS ANALYST (BI & Analytics)
ESECURITEL PVT. LTD.
06.2014 - 04.2015
- Built frameworks for data collection, analysis, and reporting to monitor key product performance metrics (KPIs) and support business decision-making.
- Partnered with business users to gather requirements, designing and developing Tableau dashboards, scorecards, and BI solutions that provided actionable insights.
- Analyzed and interpreted reporting requirements, creating prototypes and proof-of-concepts using Tableau Desktop to validate solutions before production deployment.
- Designed and implemented databases, tables, clustered/non-clustered indexes, constraints, views, and stored procedures to support analytics and reporting needs.
- Developed Fraud Prevention and Loss Scorecard applications using extensive T-SQL, SSIS, and SSRS, integrating multiple data sources for accurate and timely reporting.
- Created T-SQL scripts and SSIS packages to extract, transform, and load data from diverse sources, leveraging BCP, BULK INSERT, and SSMS for data migration.
- Operated advanced Tableau functions and expressions, connecting to external data sources via ODBC, OLEDB, and other interfaces to build comprehensive dashboards.
- Contributed to all phases of the project lifecycle, including requirements analysis, design, documentation, unit testing, defect resolution, and deployment.
- Improved MIS systems for management, clients, and internal communications by standardizing reporting procedures, reducing automation time, and enhancing accuracy.
- Utilized aggregated tables and optimized data structures to improve the efficiency of monthly and yearly reporting.
- Designed and implemented ETL workflows in SSIS, managing control flow and data flow transformations to support enterprise data warehouse operations.
- Streamlined reporting operations and delivered accurate, timely, and accessible dashboards, enabling data-driven decision-making across the organization.
SQL FRAUD ANALYST
07.2013 - 05.2014
- Designed, coded, tested, and debugged custom queries using Microsoft T-SQL and SQL Reporting Services.
- Developed and prepared quality code that met project and departmental standards.
- Key contributor to launch of 39 clients on proprietary risk analysis management platform, resulting in annualized $2M in savings.
- Originated the first fraud dashboard used for the Pre-RAMP launches and dealer analysis based on model, perils, and fulfillment method, based on trend analysis and using Advanced SQL.
- Strategic contributor of Fraud Management business requirements for fraud prevention platform within the company's newly developed claims processing software, which involves fraud attributes, rules engine logic, workflow, and notifications processes.
- Delivered client quarterly business review (QBR) reports and presentations representing the Fraud Management team.
- Enhanced departmental performance in identifying fraudulent activity by leading mentoring sessions and automating reporting structure, resulting in over $500k in savings from fraud usage and a decreased time spent per account by 24%.
- Evaluated clients’ accounts to decrease fraud losses by analyzing claims trends, which improved percentage of identified fraud from 77% to 97%, consistently exceeding goals with an average monthly savings of $60k per month.
- Performed forensic data analysis and data mining using T-SQL and SSIS to identify patterns of suspicious activity, outliers, anomalies, and other issues that represent fraud risk.
- Provided data analytics that facilitated process optimizations and systems upgrades to enhance performance.
Education
Product Management & Strategy - Product Management
The Wharton School
05.2001 -
Executive Education - Data to Decisions
Massachusetts Institute of Technology
01.2019
Master of Science - Management
Robert Gordon University
Aberdeen 05.2001 -
Master of Science - Information Technology
Kamla-Ohla College
India 05.2001 -
Skills
Databases: Bigquery, Materialise Microsoft SQL Server 2008/08/R2 & 2012 T-SQL, SQLite3, Oracle 11g (PL/SQL), Exadata,SSMS, DB2, Postgresql
undefinedCertification
Certified Google Data Analytics Professional
Timeline
Manager Data & Analytics Engineering(Product)
Prizpeiks
11.2022 - Current
Manager Data Analytics(Product)
Relay Payments
06.2022 - 11.2022
Lead Data Engineer
Chick Fil-A
09.2015 - 08.2020
SENIOR DATA ANALYST
COX ENTERPRISES-MANHEIM
09.2015 - 08.2020
SQL SERVER DEVELOPER
TRAVEL INCORPORATED
04.2015 - 08.2015
SENIOR BUSINESS ANALYST (BI & Analytics)
ESECURITEL PVT. LTD.
06.2014 - 04.2015
SQL FRAUD ANALYST
07.2013 - 05.2014
Product Management & Strategy - Product Management
The Wharton School
05.2001 -
Master of Science - Management
Robert Gordon University
05.2001 -
Master of Science - Information Technology
Kamla-Ohla College
05.2001 -
Executive Education - Data to Decisions
Massachusetts Institute of Technology
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