Database Architect

Established in 1997, Softeq was built from the ground up to specialize in new product development and R&D, tackling the most difficult problems in the tech sphere. Now we've expanded to offer early-stage innovation and ideation plus digital transformation business consulting. Our superpower is to deliver all of this under one roof on a global scale. So let's get started and build a better future together!

We are looking for a strong Data Engineer who can work with a large amount of data and prepare it for the ML pipelines, provide data analysis and visualization, and continuously perform storage optimization tasks. Experience with different types of SQL databases(MySQL/PostgreSQL/MSSQL), knowledge of JOINS, inner selects, and index specification/creation to speed up requests.

Responsibilities:

• Design, develop, and maintain scalable data pipelines and ETL processes to support analytics and business intelligence;
• Write complex SQL queries to extract, transform, and analyze large datasets from multiple sources;
• Build and maintain dashboards, reports, and other data visualizations to deliver actionable insights to business stakeholders;
• Collaborate with cross-functional teams, including engineering, product, and business units, to understand data needs and deliver robust solutions;
• Perform exploratory data analysis (EDA) to uncover trends, anomalies, and opportunities for deeper investigation;
• Ensure data quality and integrity through rigorous validation and data governance practices;
• Develop scripts and tools using languages like Python or R to automate workflows and conduct advanced data analyses;
• Support data infrastructure improvements and contribute to the overall data architecture and design;
• Document processes, data models, and pipelines for internal knowledge sharing and future reference.

Requirements:

• Proficiency in SQL with the ability to write efficient, optimized queries for complex datasets;
• Strong analytical skills with experience working with large-scale data environments (e.g., data warehouses, relational databases);
• Programming experience in Python, R, or another data-focused language;
• Familiarity with ETL tools and frameworks (e.g., Airflow, dbt, Apache NiFi);
• Experience with BI platforms such as Tableau, Power BI, Looker, or similar;
• Solid understanding of data modeling, data warehousing concepts, and database design;
• Experience working with cloud-based data platforms (e.g., AWS Redshift, Google BigQuery, Snowflake);
• Strong problem-solving abilities and attention to detail;
• Excellent communication skills with the ability to translate technical findings into business insights;
• Bachelor's degree in Computer Science, Data Science, Statistics, Engineering, or a related field (or equivalent work experience).