Data Engineer

Job Title: Data Engineer (Mid to Senior)Key ResponsibilitiesPartner with product owners, managers, and engineers to define project scopes and shape Minimum Viable Products (MVPs).Collaborate with cross-functional teams to design and implement big data solutions using technologies such as Databricks, Azure Data Factory, Spark, PySpark, Python, and SQL.Architect and develop resilient, scalable data pipelines that source information from a wide variety of inputs, including databases, APIs, applications, and file-based structures across platforms like Snowflake, Azure Synapse, AWS Redshift, and GCP BigQuery.Apply modern data architecture principles, such as microservices, event-driven design, and data lake patterns, to enhance scalability, performance, and long-term maintainability.Conduct data mapping activities, document end-to-end data lineage, and ensure full traceability through tools like Azure Purview and Lakehouse Monitoring.Education & ExperienceBachelor’s degree in Computer Science or a related discipline.At least 3-7 years of professional experience as a Data Engineer or in a closely related technical roleProficiency in programming languages such as Python, Scala, or Java, with (hands-on Spark experience preferred).Strong understanding of relational and NoSQL databases, including data modeling and advanced query writing.Hands-on experience with Big Data frameworks like Databricks, Azure Data Factory, Spark, and PySpark.Exposure to major cloud platforms such as Azure, AWS, or GCP.Experience building large-scale distributed systems, robust data pipelines, and advanced data processing workflows.Familiarity with cloud data warehouse technologies (Snowflake, Azure Synapse, AWS Redshift, or GCP BigQuery). Knowledge of CI/CD practices and IaC tools is an added advantage.Skills & AbilitiesStrong analytical mindset with the ability to interpret and visualize complex datasets.Genuine interest in Big Data technologies and modern data engineering ecosystems.Passion for leveraging data to drive insights, influence decisions, and craft compelling narratives.Ability to break down highly technical topics into language understood by non-technical stakeholders.Excellent collaboration skills and the ability to build strong relationships across teams.Working knowledge of data governance practices, data quality frameworks, and industry standards.