3 Airbyte Jobs

Who We Are For 20 years, we have been working with organizations large and small to help solve business challenges through technology. We bring a unique combination of engineering and strategy to Make Data Work for organizations. Our clients range from the travel and leisure industry to publishing, retail and banking. The common thread between our clients is their commitment to making data work as seen through their investment in those efforts. In our quest to solve data challenges for our clients, we work with large enterprise, cloud-based and marketing technology suites. We have a deep understanding of these solutions so we can help our clients make the most of their investment in an efficient way to have a data-driven business. Softcrylic now joins forces with Hexaware to Make Data Work in bigger ways! Why Work at Softcrylic? Softcrylic provides an engaging, team-focused, and rewarding work environment where people are excited about the work they do and passionate about delivering creative solutions to our clients. Work Timing: 12:30 pm to 9:30 pm (Flexible in work timing) Here's how to approach the interview: All technical interview rounds will be conducted virtually. The final round will be a face-to-face interview with HR in Chennai. However, there will be a 15-minute technical assessment/in-person technical discussion as part of the final round. Make sure to prepare accordingly for both virtual and in-person components. Job Description: 5 + years of experience in working as Data Engineer Experience in migrating existing datasets from Big Query to Databricks using Python scripts. Conduct thorough data validation and QA to ensure accuracy, completeness, parity, and consistency in reporting. Monitor the stability and status of migrated data pipelines, applying fixes as needed. Migrate data pipelines from Airflow to Airbyte/Dagster based on provided frameworks. Develop Python scripts to facilitate data migration and pipeline transformation. Perform rigorous testing on migrated data and pipelines to ensure quality and reliability. Required Skills: Strong experience in working on Python for scripting Good experience in working on Data Bricks and Big Query Familiarity with data pipeline tools such as Airflow, Airbyte, and Dagster. Strong understanding of data quality principles and validation techniques. Ability to work collaboratively with cross-functional teams. Dinesh M dinesh.m@softcrylic.com +9189255 18191

At Mitratech, we are a team of technocrats focused on building world-class products that simplify operations in the Legal, Risk, Compliance, and HR functions of Fortune 100 companies. We are a close-knit, globally dispersed team that thrives in an ecosystem that supports individual excellence and takes pride in its diverse and inclusive work culture centered around great people practices, learning opportunities, and having fun! Our culture is the ideal blend of entrepreneurial spirit and enterprise investment, enabling the chance to move at a rapid pace with some of the most complex, leading-edge technologies available. Given our continued growth, we always have room for more intellect, energy, and enthusiasm - join our global team and see why it's so special to be a part of Mitratech! Job Description We are seeking a highly motivated and skilled Analytics Engineer to join our dynamic data team. The ideal candidate will possess a strong background in data engineering and analytics, with hands-on experience in modern analytics tools such as Airbyte, Fivetran, dbt, Snowflake, Airflow, etc. This role will be pivotal in transforming raw data into valuable insights, ensuring data integrity, and optimizing our data infrastructure to support the organization's data platform. Essential Duties & Responsibilities Data Integration and ETL Processes: Design, implement, and manage ETL pipelines using tools like Airbyte and Fivetran to ensure efficient and accurate data flow from various sources into our Snowflake data warehouse. Maintain and optimize existing data integration workflows to improve performance and scalability. Data Modeling and Transformation: Develop and maintain data models using dbt / dbt Cloud to transform raw data into structured, high-quality datasets that meet business requirements. Ensure data consistency and integrity across various datasets and implement data quality checks. Data Warehousing: Manage and optimize our Redshift / Snowflake data warehouses, ensuring it meets performance, storage, and security requirements. Implement best practices for data warehouse management, including partitioning, clustering, and indexing. Collaboration and Communication: Work closely with data analysts, data scientists, and business stakeholders to understand data requirements and deliver solutions that meet their needs. Communicate complex technical concepts to non-technical stakeholders in a clear and concise manner. Continuous Improvement: Stay updated with the latest developments in data engineering and analytics tools, and evaluate their potential to enhance our data infrastructure. Identify and implement opportunities for process improvements, automation, and optimization within the data pipeline. Requirements & Skills: Education and Experience: Bachelor's degree in Computer Science, Information Systems, Data Science, or a related field. 3-5 years of experience in data engineering or analytics engineering roles. Experience in AWS and DevOps is a plus. Technical Skills: Proficiency with modern ETL tools such as Airbyte and Fivetran. Must have experience with dbt for data modeling and transformation. Extensive experience working with Snowflake or similar cloud data warehouses. Solid understanding of SQL and experience writing complex queries for data extraction and manipulation. Familiarity with Python or other programming languages used for data engineering tasks. Analytical Skills: Strong problem-solving skills and the ability to troubleshoot data-related issues. Ability to understand business requirements and translate them into technical specifications. Soft Skills: Excellent communication and collaboration skills. Strong organizational skills and the ability to manage multiple projects simultaneously. Detail-oriented with a focus on data quality and accuracy. We are an equal-opportunity employer that values diversity at all levels. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, national origin, age, sexual orientation, gender identity, disability, or veteran status.

Principal Architect - Platform & Application Architect Experience 15+ years in software/data platform architecture 5+ years in architectural leadership roles Architecture & Data Platform Expertise Education Bachelors/Master’s in CS, Engineering, or related field Title: Principal Architect Location: Onsite Bangalore Experience: 15+ years in software & data platform architecture and technology strategy Role Overview We are seeking a Platform & Application Architect to lead the design and implementation of a next-generation, multi-domain data platform and its ecosystem of applications. In this strategic and hands-on role, you will define the overall architecture, select and evolve the technology stack, and establish best practices for governance, scalability, and performance. Your responsibilities will span across the full data lifecycle—ingestion, processing, storage, and analytics—while ensuring the platform is adaptable to diverse and evolving customer needs. This role requires close collaboration with product and business teams to translate strategy into actionable, high-impact platform & products. Key Responsibilities 1. Architecture & Strategy Design the end-to-end architecture for a On-prem / hybrid data platform (data lake/lakehouse, data warehouse, streaming, and analytics components). Define and document data blueprints, data domain models, and architectural standards. Lead build vs. buy evaluations for platform components and recommend best-fit tools and technologies. 2. Data Ingestion & Processing Architect batch and real-time ingestion pipelines using tools like Kafka, Apache NiFi, Flink, or Airbyte. Oversee scalable ETL/ELT processes and orchestrators (Airflow, dbt, Dagster). Support diverse data sources: IoT, operational databases, APIs, flat files, unstructured data. 3. Storage & Modeling Define strategies for data storage and partitioning (data lakes, warehouses, Delta Lake, Iceberg, or Hudi). Develop efficient data strategies for both OLAP and OLTP workloads. Guide schema evolution, data versioning, and performance tuning. 4. Governance, Security, and Compliance Establish data governance , cataloging , and lineage tracking frameworks. Implement access controls , encryption , and audit trails to ensure compliance with DPDPA, GDPR, HIPAA, etc. Promote standardization and best practices across business units. 5. Platform Engineering & DevOps Collaborate with infrastructure and DevOps teams to define CI/CD , monitoring , and DataOps pipelines. Ensure observability, reliability, and cost efficiency of the platform. Define SLAs, capacity planning, and disaster recovery plans. 6. Collaboration & Mentorship Work closely with data engineers, scientists, analysts, and product owners to align platform capabilities with business goals. Mentor teams on architecture principles, technology choices, and operational excellence. Skills & Qualifications Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field. 12+ years of experience in software engineering, including 5+ years in architectural leadership roles. Proven expertise in designing and scaling distributed systems, microservices, APIs, and event-driven architectures using Java, Python, or Node.js. Strong hands-on experience with building scalable data platforms on premise/Hybrid/cloud environments. Deep knowledge of modern data lake and warehouse technologies (e.g., Snowflake, BigQuery, Redshift) and table formats like Delta Lake or Iceberg. Familiarity with data mesh, data fabric, and lakehouse paradigms. Strong understanding of system reliability, observability, DevSecOps practices, and platform engineering principles. Demonstrated success in leading large-scale architectural initiatives across enterprise-grade or consumer-facing platforms. Excellent communication, documentation, and presentation skills, with the ability to simplify complex concepts and influence at executive levels. Certifications such as TOGAF or AWS Solutions Architect (Professional) and experience in regulated domains (e.g., finance, healthcare, aviation) are desirable.