Data Engineer

Company Overview ALIANDO, is an award-winning Azure Expert Managed Service solutions company focused on selling and deploying Microsoft technologies for U.S. and international companies. For over 20 years, Microsoft and its partners have recommended ALIANDO, for licensing, consulting, and managed services to corporations large and small. The company offers competitive pay and comprehensive employee benefits, including health insurance, fitness allowances, work-from-home allowances, paid maternity and parental leave, and generous PTO. At ALIANDO, we aim to unleash the potential of people and technology. Our company was built around the idea that there is no success without team success. We foster a culture of inclusion and fairness where diverse interests, experiences, and backgrounds are celebrated. We strive to empower and unleash the potential of everyone to ensure that every employee has a path to success. We're in it together to make life better for each other, our customers, our partners, and our communities. About the Role We are looking for a skilled Data Engineer to design, develop, and maintain scalable data pipelines and data infrastructure that support business intelligence, analytics, and AI initiatives. The ideal candidate will have strong expertise in SQL, ETL processes, Python, and Big Data technologies, with experience building reliable, high-performance data solutions. You will collaborate with data analysts, data scientists, software engineers, and business stakeholders to ensure high-quality, accessible, and secure data for enterprise applications and reporting. Key Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines for structured and unstructured data.
• Collect, integrate, and transform data from multiple internal and external sources.
• Build and optimize data pipelines to support analytics, reporting, and AI/ML workloads.
• Develop efficient SQL queries, stored procedures, and database objects.
• Ensure data quality, consistency, integrity, and governance across data platforms.
• Design and manage data warehouses, data lakes, and enterprise data models.
• Monitor and optimize pipeline performance, reliability, and scalability.
• Implement data validation, cleansing, and quality assurance processes.
• Work with Big Data technologies to process high-volume datasets.
• Collaborate with Data Scientists to prepare datasets for machine learning models.
• Automate data workflows using Python and ETL tools.
• Troubleshoot data pipeline failures and optimize processing efficiency.
• Maintain technical documentation and data architecture standards.
• Participate in Agile ceremonies and contribute to continuous improvement initiatives. Required Skills
• Strong experience with SQL and relational databases.
• Hands-on experience with ETL/ELT development.
• Strong Python programming skills.
• Experience with Big Data technologies (Spark, Hadoop, Databricks, or similar).
• Knowledge of data warehousing concepts and dimensional modeling.
• Experience with cloud data platforms (Azure, AWS, or Google Cloud).
• Familiarity with Apache Airflow, Azure Data Factory, Informatica, SSIS, or similar ETL tools.
• Strong understanding of data governance and data quality principles.
• Experience with Git and CI/CD pipelines.
• Excellent analytical and problem-solving skills. Preferred Skills
• Azure Synapse Analytics
• Snowflake
• Redshift
• Google BigQuery
• Kafka
• Delta Lake
• Docker
• Kubernetes
• Power BI or Tableau
• Azure DevOps Qualifications
• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
• Minimum 4+ years of experience in Data Engineering or Data Integration. Preferred Certifications
• Google Professional Data Engineer
• Microsoft Certified: Azure Data Engineer Associate
• AWS Certified Data Analytics – Specialty What We're Looking For
• Strong analytical and problem-solving abilities.
• Experience building enterprise-scale data platforms.
• Excellent communication and collaboration skills.
• Strong ownership and attention to detail.
• Ability to work independently and within Agile teams.
• Passion for modern data technologies and continuous learning.