Junior Data Engineer – Data Quality & Analytics

We are seeking a motivated Junior Data Engineer to support a data modernization initiative focused on data cleansing, standardization, and system integrations across complex relational data environments. This role is ideal for someone who enjoys improving data quality, building scalable pipelines, and working in structured, high-impact data ecosystems.

Key Responsibilities

• Design and implement data pipelines for cleansing, standardizing, and validating structured and semi-structured data
• Analyze, transform, and optimize data using SQL and Python
• Build and maintain integrations with relational databases using JDBC
• Consume and integrate REST APIs for data enrichment and validation from trusted providers
• Support identity resolution, deduplication, and entity normalization workflows
• Work with large relational schemas to improve data quality, integrity, and consistency
• Collaborate with senior engineers, architects, and business stakeholders to translate business rules into scalable data solutions
• Ensure auditability, traceability, and strong data governance practices through logging and metadata management

Required Skills & Experience

• Minimum of 3 years of professional engineering experience
• Strong SQL skills and deep understanding of relational databases
• Proficiency in at least one programming language: Python, Scala, or Java
• Hands-on experience with data cleansing, validation, and data quality processes
• Experience with JDBC and relational database integrations
• Experience building or consuming RESTful APIs

Nice to Have

• Experience with data analysis using Apache Spark or Pandas
• Exposure to data lakehouse or medallion architectures (Bronze/Silver/Gold layers)
• Familiarity with identity resolution and master data management (MDM) concepts
• Experience processing semi-structured data (e.g., PDFs, OCR outputs)
• Experience working with large-scale data platforms such as Databricks, Snowflake, or cloud-based data lakes