We are looking for two Data Analysts: one specializing in data engineering & migration and another focused on data pipeline & automation. Applicants must have strong communication skills in English, both spoken and written, and all resumes should be submitted in English. Key Responsibilities Improve data pipelines with automation and quality checks to ensure accuracy, consistency, and reliability, reducing manual intervention and minimizing errors. Lead migration of legacy systems to new platforms, performing thorough analysis, seamless data transfer, integration, and performance enhancement while maintaining continuity. Requirements Required Education Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field (preferred). Equivalent hands‑on experience is highly valued. Required Experience 4 to 7 years as a Data Engineer. Practical, hands‑on expertise beyond theoretical knowledge. Required Background / Industry Experience (Both roles) Experience with cloud‑based data platforms and environments. Strong SQL skills and data modeling for data warehouses. Strong Python skills (notably in notebooks) for building and maintaining data workflows. Experience developing and maintaining ETL/ELT processes. Familiarity with data warehouses used by reporting/business teams. Version control expertise using Git/GitHub in collaborative settings. Understanding of data engineering best practices, including pipeline orchestration, dependency management, data quality, validation, and monitoring fundamentals. Required for Migration‑focused Role Hands‑on data migration experience. Schema mapping and transformation. Data reconciliation and validation (strong focus). Data quality checks, integrity validation, and issue resolution. Backfills and historical data handling. Cutover planning and execution. Required for Automation‑focused Role Experience building and maintaining automated data pipelines. Scheduling, orchestration, and failure handling. Workflow reliability, monitoring, and repeatability. Preferred Experience within Microsoft Fabric or the broader Microsoft Azure data ecosystem. Experience with orchestration tools such as Apache Airflow, Azure Data Factory, or Fabric pipelines. Experience with data quality and observability practices: validation frameworks, alerting, SLAs, monitoring. Experience optimizing performance in data environments: query tuning, partitioning, indexing, cost optimization. Familiarity with modern data formats and large‑scale processing: Parquet, Delta, incremental processing patterns. Experience integrating with external systems: REST APIs, authentication, retries, error handling. Exposure to CI/CD practices for data workflows: Git‑based deployments, PR workflows, environment promotion. Key Soft Skills Clear communication: explain data issues, trade‑offs, and results to technical and business stakeholders. Ownership & accountability: take end‑to‑end responsibility for pipelines, data quality, and outcomes. Problem‑solving mindset: debug complex data issues and resolve ambiguity independently. Collaboration: work effectively across engineering, analytics, and business teams. Adaptability: thrive in evolving environments (migration, changing requirements, new tools). Technical Skills Proficiency in SQL, Python, cloud technologies, and data competency. Benefits USD base salary. Paid Time Off (PTO) after 6 months of service. Full‑time opportunity. Completely remote work environment. Typical work schedule: 9:00 am to 6:00 pm Eastern Time, Monday through Friday, with occasional additional hours as needed. #J-18808-Ljbffr