Work with Us

Location: Hyderabad, India
Job Type: Full-time

Role Overview
We are looking to hire talented QA Automation Engineers to strengthen our QA and testing capabilities. The ideal candidates will bring solid programming expertise, hands-on testing experience, and a passion for delivering high-quality software. This document outlines the key qualifications, required skills, and evaluation criteria for the hiring process.

Key Qualifications
Technical Proficiency

• Strong knowledge of Python and PyTest for test automation
• Experience with SQL for data validation and querying
• Hands-on ETL testing experience
• Familiarity with CI/CD pipelines, particularly GitHub Actions

Testing & Process Skills

• Ability to write clear, effective, and maintainable test cases
• Experience using TestRail or similar test management tools
• Understanding of software QA methodologies and best practices

Required Skills Summary

Nice to Have

• Experience with cloud platforms (AWS, GCP, or Azure)
• Knowledge of containerization tools such as Docker or Kubernetes
• Familiarity with data pipeline frameworks (Apache Spark, Airflow)
• Understanding of Agile/Scrum development practices
• Exposure to performance or load testing tools

Evaluation Criteria
Candidates will be assessed across the following dimensions during the interview process:

• Technical interview: Python coding challenge and SQL query tasks
• Practical assessment: Writing test cases for a sample ETL scenario
• Tool knowledge: Hands-on demonstration with PyTest and CI/CD setup
• Behavioural assessment: Communication, collaboration, and problem-solving

Location: Hyderabad, India
Job Type: Full-time

Job Description
We are looking for an experienced and results-driven Data Engineer to join our growing Data Engineering team.
The ideal candidate will be proficient in building scalable, high-performance data transformation pipelines using Snowflake and dbt and be able to effectively work in a consulting setup. In this role, you will be instrumental in ingesting, transforming, and delivering high-quality data to enable data-driven decision-making across the client’s organization.

Key Responsibilities

1. Design and implement scalable ELT pipelines using dbt on Snowflake, following industry accepted best practices.
2. Build ingestion pipelines from various sources including relational databases, APIs, cloud storage and flat files into Snowflake.
3. Implement data modelling and transformation logic to support layered architecture (e.g., staging, intermediate, and mart layers or medallion architecture) to enable reliable and reusable data assets..
4. Leverage orchestration tools (e.g., Airflow,dbt Cloud, or Azure Data Factory) to schedule and monitor data workflows.
5. Apply dbt best practices: modular SQL development, testing, documentation, and version control.
6. Perform performance optimizations in dbt/Snowflake through clustering, query profiling, materialization, partitioning, and efficient SQL design.
7. Apply CI/CD and Git-based workflows for version-controlled deployments.
8. Contribute to growing internal knowledge base of dbt macros, conventions, and testing frameworks.
9. Collaborate with multiple stakeholders such as data analysts, data scientists, and data architects to understand requirements and deliver clean, validated datasets.
10. Write well-documented, maintainable code using Git for version control and CI/CD processes.
11. Participate in Agile ceremonies including sprint planning, stand-ups, and retrospectives.
12. Support consulting engagements through clear documentation, demos, and delivery of client-ready solutions.

Required Qualifications

• 3 to 5 years of experience in data engineering roles, with 2+ years of hands-on experience in Snowflake and dbt.
• Experience building and deploying dbt models in a production environment.
• Expert-level SQL and strong understanding of ELT principles. Strong understanding of ELT patterns and data modelling (Kimball/Dimensional preferred).
• Familiarity with data quality and validation techniques: dbt tests, dbt docs etc.
• Experience with Git, CI/CD, and deployment workflows in a team setting
• Familiarity with orchestrating workflows using tools like dbt Cloud, Airflow, or Azure Data Factory.
• Core Competencies:
  • Data Engineering and ELT Development:
    • Building robust and modular data pipelines using dbt.
    • Writing efficient SQL for data transformation and performance tuning in Snowflake.
    • Managing environments, sources, and deployment pipelines in dbt.
  • Cloud Data Platform Expertise:
    • Strong proficiency with Snowflake: warehouse sizing, query profiling, data loading, and performance optimization.
    • Experience working with cloud storage (Azure Data Lake, AWS S3, or GCS) for ingestion and external stages.
• Technical Toolset:
  • Languages & Frameworks:
    • Python: For data transformation, notebook development, automation.
    • SQL: Strong grasp of SQL for querying and performance tuning.
• Best Practices and Standards:
  • Knowledge of modern data architecture concepts including layered architecture (e.g., staging → intermediate → marts, Medallion architecture).Familiarity with data quality, unit testing (dbt tests), and documentation (dbt docs).
• Security & Governance:
  • Access and Permissions:
    • Understanding of access control within Snowflake (RBAC), role hierarchies, and secure data handling.
    • Familiar with data privacy policies (GDPR basics), encryption at rest/in transit.
• Deployment & Monitoring:
  • DevOps and Automation:
    • Version control using Git, experience with CI/CD practices in a data context.
    • Monitoring and logging of pipeline executions, alerting on failures.
• Soft Skills:
  • Communication & Collaboration:
    • Ability to present solutions and handle client demos/discussions.
    • Work closely with onshore and offshore team of analysts, data scientists, and architects.
    • Ability to document pipelines and transformations clearly.
    • Basic Agile/Scrum familiarity – working in sprints and logging tasks.
    • Comfort with ambiguity, competing priorities and fast-changing client environment.
• Nice to Have:
  • Experience in client-facing roles or consulting engagements.
  • Exposure to AI/ML data pipelines, feature stores,
  • Exposure to MLflow for basic ML model tracking
  • Experience/Exposure using Data quality tooling
• Education:
  • Bachelor’s or master’s degree in computer science, Data Engineering, or a related field.
  • Certifications such as Snowflake SnowPro, dbt Certified Developer Data Engineering are a plus.

Why Join Us?

• Opportunity to work on diverse and challenging projects in a consulting environment.
• Collaborative work culture that values innovation and curiosity.
• Access to cutting-edge technologies and a focus on professional development.
• Competitive compensation and benefits package.
• Be part of a dynamic team delivering impactful data solutions.

About Us
Logic Pursuits provides companies with innovative technology solutions for everyday business problems. Our passion is to help clients become intelligent, information-driven organizations, where fact-based decision-making is embedded into daily operations, which leads to better processes and outcomes. Our team combines strategic consulting services with growth-enabling technologies to evaluate risk, manage data, and leverage AI and automated processes more effectively. With deep, big four consulting experience in business transformation and efficient processes, Logic Pursuits is a game-changer in any operations strategy.

Location: Hyderabad, India
Job Type: Full-time

Job Description
We are seeking an experienced and innovative Senior Data Engineer to lead the design, development, and implementation of robust data pipelines and solutions for our clients. The ideal candidate will possess strong technical expertise, excellent leadership skills, and the drive to continuously learn and innovate.
As a Senior Data Engineer, you will lead a team of 3 to 5 talented engineers, ensuring high-quality deliverables while fostering a culture of innovation, collaboration, and technical excellence. You will also coordinate with clients to gather requirements, design technical solutions, and drive seamless project execution.

Key Responsibilities

1. Data Pipeline Development:
   • Design, build, and optimize scalable data pipelines to process and transform large datasets.
   • Implement best practices in ETL/ELT processes, data integration, and data warehousing.
2. Team Leadership:
   • Lead, mentor, and manage a team of 3 to 5 data engineers.
   • Review team members’ work to ensure adherence to technical standards and project timelines.
   • Provide technical guidance and foster skill development within the team.
3. Client Collaboration:
   • Work closely with clients to understand business requirements and translate them into technical solutions.
   • Communicate effectively with stakeholders to ensure alignment on project goals, timelines, and deliverables.
4. Quality Assurance and Innovation:
   • Conduct code reviews and validations to maintain high-quality standards and optimize system performance.
   • Identify opportunities for innovation and implement cutting-edge technologies in data engineering.
5. Internal Initiatives and Eminence Building:
   • Drive internal initiatives to improve processes, frameworks, and methodologies.
   • Contribute to the organization’s eminence by developing thought leadership, sharing best practices, and participating in knowledge-sharing activities.
6. Learning and Adaptability:
   • Stay updated with emerging data technologies, frameworks, and tools.
   • Actively explore and integrate new technologies to improve existing workflows and solutions.
   • Exhibit a “figure it out” attitude, taking ownership and accountability for challenges and solutions.

Qualifications

• Education:
  • Bachelor’s or Master’s degree in computer science, Data Engineering, or a related field.
  • Certifications in cloud platforms such as Snowflake Snowpro, Azure Data Engineer is a plus.
• Experience:
  • 5 to 8 years of experience in data engineering with a strong focus on pipeline development and data modeling.
  • Proven experience in leading small teams or mentoring junior engineers.
• Technical Skills:
  • Expertise in programming languages such as Python, Scala, or Java.
  • Proficiency in designing and constructing data pipelines for ingesting raw data into Cloud Data Warehouses (e.g., Snowflake, Redshift), cleansing and transforming data to meet required specifications using various ETL/ELT tools such as Matillion, dbt, Striim, etc.
  • Hands-on experience with relational and NoSQL databases and data modeling techniques.
  • Hands-on experience of 2+ years in designing and developing data integration solutions using Matillion and/or dbt.
  • Strong knowledge of data engineering and integration frameworks.
  • Successfully implemented at least one end-to-end project with multiple transformation layers.
  • Good grasp of coding standards, with the ability to define standards and testing strategies for projects.
  • Proficiency in working with cloud platforms (AWS, Azure, GCP) and associated data services.
  • Enthusiastic about working in Agile methodology.
  • Possess a comprehensive understanding of the DevOps process including GitHub integration and CI/CD pipelines.
  • Familiarity with containerization (Docker), and orchestration tools (such as Airflow, Control-M).
• Soft Skills:
  • Excellent problem-solving and analytical skills.
  • Strong communication & interpersonal skills to liaise effectively with clients and team members.
  • Demonstrated accountability, ownership, and a proactive approach to solving problems.
  • A proactive mindset with the ability to adapt to new technologies and frameworks.

Why Join Us?

• Opportunity to work on challenging and innovative projects.
• A collaborative environment that values creativity and continuous learning.
• Competitive salary and benefits package.
• A chance to make a significant impact by shaping the future of data-driven solutions.

About Us
Logic Pursuits provides companies with innovative technology solutions for everyday business problems. Our passion is to help clients become intelligent, information-driven organizations, where fact-based decision-making is embedded into daily operations, which leads to better processes and outcomes. Our team combines strategic consulting services with growth-enabling technologies to evaluate risk, manage data, and leverage AI and automated processes more effectively. With deep, big four consulting experience in business transformation and efficient processes, Logic Pursuits is a game-changer in any operations strategy.

Location: Hyderabad, India
Job Type: Full-time

Expected Joining Time: Immediate to 30 days.
Potential companies: Tiger Analytics, Tredence, Quantiphi, Data Engineering Group within Infosys/TCS/Cognizant, Deloitte Consulting etc.

About the Role:
This position requires someone with good problem solving, business understanding and client presence. Overall professional experience of the candidate should be above 8 years. A minimum of 5 years of experience in leading and managing a client portfolio in Data Engineering space. Should have good understanding of business operations, challenges faced, and business technology used across business functions.
The candidate must understand the usage of traditional and modern data Engineering technologies/tools for solving business problems and help clients in their data journey. The candidate must have knowledge of emerging technologies for data management including data governance, data quality, security, data integration, processing, and provisioning. The candidate must possess required soft skills to work with teams and lead medium to large teams.
Candidate should be comfortable with taking leadership roles, in client projects, presales/consulting, solutioning, business development conversations, execution on data engineering projects.

Key Responsibilities:

• Client Engagement & Relationship Management:
  • Serve as the primary point of contact for clients on data engineering projects, understanding their needs, challenges, and goals.
  • Develop and maintain strong client relationships, ensuring high levels of client satisfaction and repeat business.
  • Translate client requirements into actionable technical solutions and project plans.
• Project Management & Delivery:
  • Oversee the delivery of data engineering projects from inception to completion, ensuring projects are delivered on time, within scope, and within budget.
  • Manage project resources, timelines, and risks, ensuring smooth project execution and delivery.
  • Collaborate with cross-functional teams including data scientists, business analysts, and IT professionals to deliver comprehensive data solutions.
• Technical Leadership & Innovation:
  • Lead the design, development, and deployment of scalable data architectures, pipelines, and processes tailored to client needs.
  • Stay abreast of industry trends, technologies, and best practices, and implement them in client projects to drive innovation and competitive advantage.
  • Provide technical oversight and guidance to the data engineering team, ensuring the adoption of best practices and high-quality output.
• Team Leadership & Development:
  • Lead, mentor, and manage a team of data engineers, fostering a collaborative and high-performance culture.
  • Provide professional development opportunities, coaching, and career growth support to team members.
  • Ensure the team is equipped with the necessary skills and tools to deliver high-quality consulting services.
• Data Governance & Quality Assurance:
  • Implement and oversee data governance frameworks, ensuring data integrity, security, and compliance across all client projects.
  • Establish and enforce data quality standards, ensuring the reliability and accuracy of data used in client solutions.
• Business Development & Consulting:
  • Support business development efforts by contributing to proposals, presenting solutions to prospective clients, and identifying opportunities for expanding client engagements.
  • Provide thought leadership in data engineering, contributing to white papers, webinars, and conferences to enhance the company’s reputation in the industry.

Experience candidates should bring

• 8 to 12 years of data engineering experience with at least 3 years in a managerial role within a consulting or professional services environment.
• Proven experience in managing multiple, complex data engineering projects simultaneously.
• Experience in leading a team of 8 to 12 professionals.
• Strong problem-solving skills and the ability to handle complex, ambiguous situations.
• Exceptional project management skills, with experience in Agile methodologies.
• A client-service mindset and a desire to take on tough and challenging projects
• Effective communication skills, both written and verbal
• Ability to work effectively across functions and levels; comfort collaborating with teammates in a virtual environment.