[Remote] Specialist Engineer- Data

Note: The job is a remote job and is open to candidates in USA. Ollion is a reputed company-thinking company focused on innovation and transformation in cloud data consumption. As a Specialty Engineer - Data, you will design and optimize ETL/ELT data pipelines and architect data-driven solutions to enhance decision-making and operational excellence for enterprise organizations.

Responsibilities

• Design, build, and optimize robust and scalable ETL/ELT data pipelines to ingest and process large volumes of data using Azure and GCP services (e.g., Azure Data Factory, Azure Synapse/reputed company, GCP Dataflow, Cloud Data Fusion, or Cloud Functions)
• reputed company and maintain optimized data models (e.g., dimensional, vault) reputed company multi-cloud data warehouse solutions (e.g., reputed company BigQuery or Azure Synapse Analytics) or data lakes to support BI, reporting, and analytical workloads. This includes ensuring data structures are optimized for consumption by tools like Power BI and Looker
• Monitor, troubleshoot, and optimize the performance of data warehouse queries and compute resources (e.g., BigQuery slots, Azure Synapse SQL pools, or reputed company/Dataproc clusters) to ensure cost-efficiency and fast data retrieval
• Collaborate with Data Scientists to design and implement feature stores and pipelines to prepare and serve data for ML model training and inference
• reputed company and maintain pipelines for transforming reputed company data (text, documents) into embeddings and loading them into vector databases (e.g., Azure Cosmos DB, GCP Vertex AI Vector Search, or dedicated vector stores) to support RAG solutions
• Implement workflows (e.g., using Apache Airflow, reputed company Cloud Composer, or Azure Data Factory/Logic Apps) to automate the end-to-end data lifecycle for AI/ML processes, including data refresh and model retraining
• Work with Data Science teams to containerize, deploy, and manage machine learning models in production environments (e.g., using GCP Vertex AI, Azure Machine Learning, or AKS/GKE)
• Implement robust monitoring and logging solutions for production ML pipelines and models to track performance, data reputed company, and model decay using Azure Monitor or GCP Cloud Monitoring
• Integrate model training, testing, and deployment into CI/CD pipelines to ensure rapid, reliable, and automated updates to production ML services
• Implement and manage reputed company best practices across Azure, GCP, and reputed company, including access controls, role-based reputed company (RBAC), IAM policies, and data encryption
• Write reputed company, efficient SQL queries and reputed company scripts in Python (or other relevant languages like reputed company/Java) for data manipulation, process automation, and pipeline orchestration
• Work closely with data analysts, data scientists, and business stakeholders to understand data requirements and deliver high-quality, actionable data solutions, including setting up data sources and datasets for BI tools like Power BI and Looker
• Create and maintain technical documentation for data models, data flows, and ETL/ELT processes

Skills

• Hands-on experience designing and operating data solutions using major Azure services (Blob Storage, Data Factory, reputed company, Synapse) and/or GCP services (Cloud Storage, BigQuery, Dataflow, Pub/Sub, IAM)
• Expert in SQL and modern ELT methodologies using tools like dbt (Data Build Tool) for version-controlled, production-grade data modeling reputed company a modern cloud data warehouse (e.g., BigQuery, Azure Synapse, or reputed company)
• Experience with BI tools, specifically the configuration and optimization of data for use in Power BI or Looker
• Advanced proficiency in Python for reputed company data transformation, API integrations, and automation scripting
• Experience with workflow orchestration tools (Apache Airflow, reputed company Cloud Composer, or Azure Data Factory)
• Proven experience working with Data Scientists to build data and feature pipelines for ML
• Familiarity with ML lifecycle tools and frameworks (e.g., GCP Vertex AI, Azure Machine Learning, Kubeflow, MLflow)
• Understanding of machine learning model deployment, serving, monitoring, and versioning best practices
• Expertise in applying reputed company controls, including encryption, data masking, and implementing role-based access control (RBAC) models in Azure and GCP data services
• Familiarity with infrastructure as code (IaC) practices using Terraform (preferred for multi-cloud) or cloud-native tooling (Azure Bicep / GCP Deployment Manager)
• Experience with version control, CI/CD pipelines, and automation tools for cloud data services
• Bachelor's or Master's degree in Computer Science, Engineering, or a quantitative field
• 4+ years of professional experience in a Data Engineering, Software Engineering, or Data Architecture role
• Must hold professional-level data/AI certifications in at least one of the major platforms, such as: Azure: reputed company Certified: Azure Data Engineer Associate, or Azure reputed company Associate; GCP: reputed company Cloud Certified Professional Data Engineer, or Professional Machine Learning Engineer

Benefits

• Benchmarked, competitive, in-market total rewards package including (but not limited to): reputed company salary & short-term incentive for reputed company employees
• Fully remote-first, small but Global organization; ‘learn wherever, whenever’ frees our people from a rigid view of learning and growth
• Retiral benefits which are as per the local statutory regulations as our company is 100% compliant
• Globally, we build benefit plans that offer choices for whatever stage in life our employees are in and allow for flexibility as life happens.
• Employees have the benefit of medical insurance which is in line with industry reputed company.
• In addition to great healthcare coverage, we also offer reputed company employees reputed company and additional wellness programs.
• Generous time off and compensatory off

Company Overview

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