Senior Data Engineer

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Teamified

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 2021

🤝 B2B

👥 HR Tech

🎯 Recruiter

B2B • HR Tech • Recruitment

Teamified is a global talent powerhouse that specializes in connecting businesses to offshore talent. They offer a comprehensive platform that simplifies the hiring process by providing access to a diverse range of skilled professionals from multiple industries. With a focus on data security and a people-first approach, Teamified aims to reduce hiring times and costs while ensuring high-quality talent matches for organizations.

📋 Description

• Design, build, and maintain scalable and secure cloud-native data platforms and data pipelines. • Lead the architecture, optimization, and operational management of the Snowflake data warehouse platform. • Develop robust ELT/ETL pipelines to ingest, transform, and deliver high-quality data from multiple internal and external sources. • Build reusable and maintainable data frameworks, transformation models, and orchestration workflows. • Develop and maintain infrastructure-as-code and automation for data platform provisioning and management where appropriate. • Optimize performance, scalability, and cost efficiency across data storage, transformation, and query workloads. • Support near real-time and batch-based data processing requirements. • Own and continuously improve Snowflake architecture, performance tuning, security, governance, and operational best practices. • Design and optimize Snowflake schemas, warehouses, clustering strategies, and data sharing capabilities. • Implement scalable data modelling approaches including dimensional modelling and data vault methodologies where appropriate. • Manage Snowflake access controls, roles, permissions, and secure data sharing practices. • Monitor Snowflake usage, query performance, and cost consumption to drive optimization initiatives. • Support data lifecycle management, retention, and governance policies within Snowflake. • Design and maintain curated, trusted, and scalable data models to support analytics, reporting, and operational use cases. • Partner with analysts, business stakeholders, and engineering teams to translate business requirements into scalable data solutions. • Enable self-service analytics capabilities through well-structured semantic layers and governed datasets. • Support and optimize BI and reporting platforms such as Looker, Power BI, or equivalent tools. • Ensure data structures and models support both operational reporting and strategic analytics requirements. • Implement data quality controls, validation frameworks, reconciliation processes, and monitoring capabilities. • Proactively identify and resolve data integrity, consistency, and performance issues. • Establish observability and operational monitoring for data pipelines and platform reliability. • Contribute to data governance, lineage, cataloguing, and metadata management practices. • Ensure data platforms and engineering processes comply with security, privacy, and regulatory requirements. • Collaborate closely with Product, Engineering, Operations, Finance, and Business stakeholders to deliver impactful data solutions. • Mentor and support junior engineers and analysts within the broader data function. • Contribute to data engineering standards, best practices, and platform strategy. • Drive continuous improvement initiatives across data architecture, tooling, and delivery practices. • Work cross-functionally to improve organizational data literacy and data maturity.

🎯 Requirements

• 5+ years of experience in Data Engineering, Analytics Engineering, or related data platform roles. • Experience designing and supporting multi-region and enterprise-scale data platform architectures. • Strong experience driving performance optimization and cloud cost efficiency initiatives across large-scale data workloads. • Strong understanding of platform reliability, operational maturity, resilience, and production support practices. • Experience implementing advanced governance, security, access control, and data protection models within enterprise data platforms. • Strong capability in developing architectural standards, engineering documentation, and scalable platform design patterns. • Strong hands-on expertise with Snowflake in enterprise-scale environments. • Advanced SQL skills with experience optimizing complex analytical queries and data transformations. • Strong experience building and maintaining modern ELT/ETL pipelines and orchestration workflows. • Strong understanding of modern data warehousing concepts, dimensional modelling, and scalable data architecture. • Experience working with cloud platforms such as AWS, Azure, or GCP. • Experience with data transformation and orchestration tools such as dbt, Airflow, Fivetran, Matillion, or equivalent platforms. • Experience integrating structured and semi-structured data sources. • Strong understanding of data governance, security, and access management principles. • Proven ability to manage large and complex datasets in production environments. • Strong analytical, troubleshooting, and problem-solving capabilities. • Excellent communication and stakeholder engagement skills. • Ability to work effectively in fast-paced, agile, and collaborative environments.

🏖️ Benefits

• Flexibility in work hours and location, with a focus on managing energy rather than time. • Access to online learning platforms and a budget for professional development • A collaborative, no-silos environment, encouraging learning and growth across teams • A dynamic social culture with team lunches, social events, and opportunities for creative input • Health insurance • Leave Benefits • 13th Month Salary