Job Title: Data Engineer (Snowflake + dbt) 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 Design and build robust ELT pipelines using dbt on Snowflake, including ingestion from relational databases, APIs, cloud storage, and flat files. Reverse-engineer and optimize SAP Data Services (SAP DS) jobs to support scalable migration to cloud-based data platforms. Implement layered data architectures (e.g., staging, intermediate, mart layers) to enable reliable and reusable data assets. Enhance dbt/Snowflake workflows through performance optimization techniques such as clustering, partitioning, query profiling, and efficient SQL design. Use orchestration tools like Airflow, dbt Cloud, and Control-M to schedule, monitor, and manage data workflows. Apply modular SQL practices, testing, documentation, and Git-based CI/CD workflows for version-controlled, maintainable code. Collaborate with data analysts, scientists, and architects to gather requirements, document solutions, and deliver validated datasets. Contribute to internal knowledge sharing through reusable dbt components and participate in Agile ceremonies to support consulting delivery. Required Qualifications Data Engineering Skills 3–5 years of experience in data engineering, with hands-on experience in Snowflake and basic to intermediate proficiency in dbt. Capable of building and maintaining ELT pipelines using dbt and Snowflake with guidance on architecture and best practices. Understanding of ELT principles and foundational knowledge of data modeling techniques (preferably Kimball/Dimensional). Intermediate experience with SAP Data Services (SAP DS) , including extracting, transforming, and integrating data from legacy systems. Proficient in SQL for data transformation and basic performance tuning in Snowflake (e.g., clustering, partitioning, materializations). Familiar with workflow orchestration tools like dbt Cloud, Airflow, or Control M. Experience using Git for version control and exposure to CI/CD workflows in team environments. Exposure to cloud storage solutions such as Azure Data Lake, AWS S3, or GCS for ingestion and external staging in Snowflake. Working knowledge of Python for basic automation and data manipulation tasks. Understanding of Snowflake's role-based access control (RBAC), data security features, and general data privacy practices like GDPR. Data Quality & Documentation Familiar with dbt testing and documentation practices (e.g., dbt tests, dbt docs). Awareness of standard data validation and monitoring techniques for reliable pipeline development. Soft Skills & Collaboration Strong problem-solving skills and ability to debug SQL and transformation logic effectively. Able to document work clearly and communicate technical solutions to a cross-functional team. Experience working in Agile settings, participating in sprints, and handling shifting priorities. Comfortable collaborating with analysts, data scientists, and architects across onshore/offshore teams. High attention to detail, proactive attitude, and adaptability in dynamic project environments. Nice to Have Experience working in client-facing or consulting roles. Exposure to AI/ML data pipelines or tools like feature stores and MLflow. Familiarity with enterprise-grade data quality tools 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. 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. Show more Show less

Job Title : Data Engineering - Manager Location: Hyderabad Position 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. Show more Show less

Job Title: Data Engineering Lead Job Type: Full-time Location: Hyderabad Expected Joining Time: Immediate to 30 days Job Description We are looking for an accomplished and dynamic Data Engineering Lead to join our team and drive the design, development, and delivery of cutting-edge data solutions. This role requires a balance of strong technical expertise, strategic leadership, and a consulting mindset. As the Lead Data Engineer, you will oversee the design and development of robust data pipelines and systems, manage and mentor a team of 5 to 7 engineers, and play a critical role in architecting innovative solutions tailored to client needs. You will lead by example, fostering a culture of accountability, ownership, and continuous improvement while delivering impactful, scalable data solutions in a fast-paced, consulting environment. Key Responsibilities Client Collaboration: Act as the primary point of contact for US-based clients, ensuring alignment on project goals, timelines, and deliverables. Engage with stakeholders to understand requirements and ensure alignment throughout the project lifecycle. Present technical concepts and designs to both technical and non-technical audiences. Communicate effectively with stakeholders to ensure alignment on project goals, timelines, and deliverables. Set realistic expectations with clients and proactively address concerns or risks. Data Solution Design and Development: Architect, design, and implement end-to-end data pipelines and systems that handle large-scale, complex datasets. Ensure optimal system architecture for performance, scalability, and reliability. Evaluate and integrate new technologies to enhance existing solutions. Implement best practices in ETL/ELT processes, data integration, and data warehousing. Project Leadership and Delivery: Lead technical project execution, ensuring timelines and deliverables are met with high quality. Collaborate with cross-functional teams to align business goals with technical solutions. Act as the primary point of contact for clients, translating business requirements into actionable technical strategies. Team Leadership and Development: Manage, mentor, and grow a team of 5 to 7 data engineers; Ensure timely follow-ups on action items and maintain seamless communication across time zones. Conduct code reviews, validations, and provide feedback to ensure adherence to technical standards. Provide technical guidance and foster an environment of continuous learning, innovation, and collaboration. Support collaboration and alignment between the client and delivery teams. Optimization and Performance Tuning: Be hands-on in developing, testing, and documenting data pipelines and solutions as needed. Analyze and optimize existing data workflows for performance and cost-efficiency. Troubleshoot and resolve complex technical issues within data systems. Adaptability and Innovation: Embrace a consulting mindset with the ability to quickly learn and adopt new tools, technologies, and frameworks. Identify opportunities for innovation and implement cutting-edge technologies in data engineering. Exhibit a "figure it out" attitude, taking ownership and accountability for challenges and solutions. Learning and Adaptability: Stay updated with emerging data technologies, frameworks, and tools. Actively explore and integrate new technologies to improve existing workflows and solutions. 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. 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, Data Engineer is a plus. Experience: 8+ years of experience in data engineering with hands-on expertise in data pipeline development, architecture, and system optimization. Demonstrated success in managing global teams, especially across US and India time zones. Proven track record in leading data engineering teams and managing end-to-end project delivery. Strong background in data warehousing and familiarity with tools such as Matillion, dbt, Striim, etc. Technical Skills: Lead the design, development, and deployment of scalable data architectures, pipelines, and processes tailored to client needs Expertise in programming languages such as Python, Scala, or Java. Proficiency in designing and delivering data pipelines in Cloud Data Warehouses (e.g., Snowflake, Redshift), using various ETL/ELT tools such as Matillion, dbt, Striim, etc. Solid understanding of database systems (relational and NoSQL) 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. Expertise in architecting data solutions. Successfully implemented at least two end-to-end projects 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. Soft Skills: Exceptional problem-solving and analytical skills. Strong communication and interpersonal skills to manage client relationships and team dynamics. Ability to thrive in a consulting environment, quickly adapting to new challenges and domains. Ability to handle ambiguity and proactively take ownership of challenges. Demonstrated accountability, ownership, and a proactive approach to solving problems. Why Join Us? Be at the forefront of data innovation and lead impactful projects. Work with a collaborative and forward-thinking team. Opportunity to mentor and develop talent in the data engineering space. Competitive compensation and benefits package. A dynamic environment where your contributions directly shape the future of data driven decision-making. 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. Show more Show less