Data Engineer

🗂 We’re Hiring: Data Engineer

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Employment Type:

Full-Time

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Level:

Mid-Level to Senior

We are seeking a skilled and analytical

Data Engineer

to design, develop, and maintain scalable data infrastructure, pipelines, and systems that support business intelligence, analytics, and data-driven decision-making. This role will work closely with Data Scientists, Analysts, Software Engineers, and business stakeholders to ensure data is reliable, accessible, secure, and optimized for organizational needs.

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Key Responsibilities

• Design, develop, and maintain scalable data pipelines and data processing systems.

• Build and optimize ETL and ELT processes for collecting, transforming, and integrating data from multiple sources.

• Develop and maintain data warehouses, data lakes, databases, and data platforms.

• Integrate data from APIs, applications, databases, cloud platforms, and third-party systems.

• Develop complex SQL queries, data transformations, stored procedures, and data processing workflows.

• Ensure data quality, accuracy, consistency, availability, and security across data platforms.

• Monitor data pipelines and infrastructure performance and troubleshoot data-related issues.

• Identify and resolve data quality problems, pipeline failures, performance bottlenecks, and integration issues.

• Design efficient data models, schemas, tables, and data structures to support analytical and operational requirements.

• Collaborate with Data Analysts and Data Scientists to prepare high-quality datasets for reporting, analytics, and machine learning initiatives.

• Support the development of dashboards, reports, and business intelligence solutions by providing reliable and well-structured data.

• Implement data validation, monitoring, testing, and governance processes.

• Optimize data processing performance, storage efficiency, and infrastructure costs.

• Support cloud-based data engineering solutions using platforms such as AWS, Microsoft Azure, or Google Cloud.

• Maintain technical documentation covering data pipelines, architectures, processes, integrations, and data models.

• Participate in data migration, platform modernization, system integration, and digital transformation projects.

• Stay updated with emerging data engineering technologies, cloud platforms, frameworks, and industry best practices.

✅ Requirements

• Proven experience in Data Engineering, Data Development, Software Engineering, or a related technical role.

• Strong proficiency in SQL and experience working with relational and non-relational databases.

• Experience developing ETL/ELT pipelines and data integration solutions.

• Strong understanding of data modeling, database design, data warehousing, and data architecture.

• Experience with programming languages such as Python, Java, Scala, or similar technologies.

• Familiarity with data engineering tools and frameworks such as Apache Spark, Airflow, Kafka, dbt, or similar platforms is an advantage.

• Experience with cloud data platforms such as AWS, Microsoft Azure, or Google Cloud is preferred.

• Strong understanding of data quality, data governance, security, and access control principles.

• Experience with data warehouses or platforms such as Snowflake, BigQuery, Redshift, Databricks, or similar technologies is an advantage.

• Strong analytical and problem-solving skills with excellent attention to detail.

• Familiarity with Git, CI/CD, version control, and software development practices.

• Ability to work effectively with Data Scientists, Data Analysts, Software Engineers, IT teams, and business stakeholders.

• Strong communication and documentation skills.

• Bachelor’s degree in Computer Science, Data Engineering, Information Technology, Software Engineering, Mathematics, or a related field is preferred.

• Relevant cloud, database, or data engineering certifications are an advantage.

🌟 What We Offer

• Opportunity to build and manage scalable data infrastructure supporting business-critical applications and analytics.

• Exposure to cloud computing, data platforms, big data technologies, data architecture, business intelligence, and machine learning.

• Opportunity to work on data-driven transformation and large-scale technology initiatives.

• Career progression into Senior Data Engineer, Data Architect, Analytics Engineer, Cloud Data Engineer, Data Platform Engineer, Lead Data Engineer, or Data Engineering Manager

roles.

• A technology-driven, collaborative, and innovation-focused work environment.

• Training, mentorship, and professional development opportunities.

• • Competitive compensation and comprehensive benefits package.