Tiger Analytics is a fast-growing advanced analytics consulting firm. Our consultants bring deep expertise in Data Science, Machine Learning and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner. We are looking for top-notch talent as we continue to build the best global analytics consulting team in the world.

The Data Engineer will be responsible for architecting, designing, and implementing advanced analytics capabilities. The right candidate will have broad skills in database design, be comfortable dealing with large and complex data sets, have experience building self-service dashboards, be comfortable using visualization tools, and be able to apply your skills to generate insights that help solve business challenges.We are looking for someone who can bring their vision to the table and implement positive change in taking the company's data analytics to the next level.

Requirements

Key Responsibilities:

Data Integration:

Implement and maintain data synchronization between on-premises Oracle databases and Snowflake using Kafka and CDC tools.

Support Data Modeling:

Assist in developing and optimizing the data model for Snowflake, ensuring it supports our analytics and reporting requirements.

Tiger Analytics is a fast-growing advanced analytics consulting firm. Our consultants bring deep expertise in Data Science, Machine Learning and AI. We are the trusted analytics partner for several Fortune 100 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner. We are looking for top-notch talent as we continue to build the best analytics global consulting team in the world.

We are seeking an experienced Data Engineer to join our data team. As a Data Engineer, you will be responsible for designing, building, and maintaining data pipelines, data integration processes, and data infrastructure using Dataiku. You will collaborate closely with data scientists, analysts, and other stakeholders to ensure efficient data flow and support data-driven decision making across the organization.

Requirements

Tiger Analytics is a fast-growing advanced analytics consulting firm. Our consultants bring deep expertise in Data Engineering, Data Science, Machine Learning and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner. We are looking for top-notch talent as we continue to build the best global analytics consulting team in the world.

As an AWS Data Engineer, you will be responsible for designing, building, and maintaining scalable data pipelines on AWS cloud infrastructure. You will work closely with cross-functional teams to support data analytics, machine learning, and business intelligence initiatives. The ideal candidate will have strong experience with AWS services, Databricks, and Snowflake.

Key Responsibilities:

InfyStrat is seeking a dedicated Data Engineer to join our data team and contribute to the development and maintenance of our robust data infrastructure. In this role, you will be responsible for designing, constructing, and optimizing data pipelines that ensure the seamless flow of data across our systems. You will work closely with data scientists, analysts, and business stakeholders to understand their data needs and provide solutions that meet those requirements. The ideal candidate will have a strong background in data engineering principles and practices, along with experience in modern data processing tools and technologies. At InfyStrat, we believe in fostering a culture of innovation and collaboration, where your contributions will have a meaningful impact on our business and data strategy. If you are passionate about building data solutions and eager to grow your career, we invite you to apply.

About Jobgether

Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching.

One of our companies is currently looking for a Data Engineer II in United States.

As a Data Engineer II, you will play a critical role in building and maintaining the data platform that drives business insights and operations. This role requires collaboration across teams to deliver secure, reliable, and scalable data pipelines. You will work closely with engineers, data scientists, and product managers to build out systems that support data-driven decision-making and optimize data flows across the organization. This position offers an exciting opportunity to contribute to the creation of an enterprise-grade data platform from the ground up, in a fast-paced, mission-driven environment.

Accountabilities:

About Jobgether

Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching.

One of our companies is currently looking for a Staff Data Engineer in the United States.

This role is ideal for a highly skilled and motivated data engineer with expertise in data lake development, distributed processing, and enterprise-level data integration. You will be responsible for designing, building, and maintaining secure and scalable data pipelines while collaborating with cross-functional teams across analytics, engineering, and AI. This is a hands-on position where you’ll contribute to architectural discussions, drive improvements in data accessibility and quality, and support mission-critical decision-making with reliable data infrastructure. If you're passionate about building data systems that scale and perform in a fast-paced, innovative environment, this opportunity is for you.

Accountabilities:

About Jobgether

Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching.

One of our companies is currently looking for a Senior Software Engineer, Data in the United Kingdom.

This role offers an exciting opportunity for an experienced data engineer to help shape the future of scientific discovery by building and evolving a cutting-edge Knowledge Graph and data infrastructure. You’ll be part of a collaborative team focused on scaling data pipelines, integrating complex public life science datasets, and enabling downstream applications through advanced data modeling and transformation. Working closely with experts across engineering, machine learning, and science, you'll develop scalable, production-grade solutions while influencing product direction through a technical and data-first perspective. This is a high-impact position where your work directly contributes to meaningful advancements in biomedical research.

Accountabilities:

Tiger Analytics is a fast-growing advanced analytics consulting firm. Our consultants bring deep expertise in Data Science, Machine Learning and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner. We are looking for top-notch talent as we continue to build the best global analytics consulting team in the world.

As a Lead Data Engineer, you will be responsible for designing, building, and maintaining scalable data pipelines on AWS cloud infrastructure. You will work closely with cross-functional teams to support data analytics, machine learning, and business intelligence initiatives. The ideal candidate will have strong experience with AWS services, Databricks, and Apache Airflow.

Key Responsibilities:

About Jobgether

Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching.

One of our companies is currently looking for a Senior Software Engineer - Data Engineering in India.

This role offers an exciting opportunity for a seasoned data engineer to design, build, and optimize robust, scalable data pipelines that support AI-driven analytics and large-scale data processing. You’ll work with technologies such as Apache Spark, Kafka, and Databricks to develop real-time and batch solutions, integrate machine learning models, and contribute to the company’s growing data infrastructure. Collaboration with cross-functional teams including data science and product engineering will be key as you build systems that drive innovation and performance across a global user base.

Accountabilities:

About Jobgether

Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching.

One of our companies is currently looking for a Data Engineer in Poland.

This is an exciting opportunity to be part of a forward-thinking team working on a data-driven product designed to transform financial management for users across the globe. You’ll be joining a dynamic, fast-paced environment where innovation and autonomy are encouraged, and your work will have a direct impact on the development of a modern data platform. As a Data Engineer, you'll take ownership of scalable data pipelines, implement cloud-based solutions, and help shape the foundation for advanced analytics and machine learning use cases.

Accountabilities:

• Design, build, and maintain a modern cloud-based Data Platform.
• Develop scalable and efficient pipelines for data ingestion and processing from various sources.
• Collaborate with cross-functional teams to support data-driven decisions and product innovation.
• Ensure high standards of data observability, quality, and reliability across the ecosystem.
• Contribute to AI/ML data infrastructure and support experimentation workflows.
• Drive improvements in orchestration, cloud resource management, and data operations.