Technical Leadership
- Collaborate with solution architects and stakeholders to understand business domains, assess requirements, and design scalable data architectures.
- Lead technical planning, development, and testing strategies during pre-sales and pre-execution readiness stages.
- Provide mentorship and guidance to junior data engineers, promoting best practices and continuous learning.
Project Delivery & Execution
- Architect, implement, and maintain efficient data pipelines and ETL processes using modern technologies.
- Review development outputs and ensure high-quality, performant, and maintainable solutions.
- Manage data loading strategies, testing execution, and historical data migrations.
Quality Assurance & Go-Live Support
- Drive unit, performance, and user acceptance testing (UAT), ensuring full traceability to business requirements.
- Lead go-live efforts including data validation, system handover, and post-implementation support.
- Ensure timely delivery and smooth transition of solutions to support teams or end users.
Technical Competencies
- Data Modeling: Expertise in relational, dimensional, and NoSQL data modeling techniques.
- ETL & Data Pipelines: Proficient in building scalable and optimized ETL workflows for structured and unstructured data.
- Data Warehousing: Deep knowledge of data warehousing principles and technologies (e.g., partitioning, indexing, schema design).
- Big Data Technologies: Familiarity with Hadoop, Spark, Kafka, Hive, or similar distributed processing frameworks
- Databases: Experience with SQL Server, Oracle, PostgreSQL, MySQL, MongoDB, or other DBMS platforms.
- Programming: Strong skills in Python, Java, Scala, or SQL for scripting, data transformation, and automation.
- Cloud Platforms: Hands-on experience with AWS, Azure, or GCP tools and services (e.g., Redshift, BigQuery, Azure Data Lake).
- Version Control: Proficient in Git for collaborative development, code versioning, and release management.
- Data Quality Assurance: Knowledge of data validation and error-handling practices to ensure high data integrity.
Qualifications
- A BSc or master’s degree in a relevant field such as Computer Science, Statistics,
Mathematics, or a related discipline. - At least 3+ years of developer-level multiple project experience
- At least one intermediate-level certification in data analytics.
- Experience in handling customers at the developer level.
- Proven track record in bringing innovative technological solutions for project-related tasks.
