Lead Data Engineer (S03/S04)

About US:

Systango Technologies Limited (NSE: SYSTANGO) is a digital engineering company that offers enterprise-class IT and product engineering services to different size organizations. At Systango, we have a culture of efficiency - we use the best-in-breed technologies to commit quality at speed and world-class support to address critical business challenges. We leverage Gen AI, AI/Machine Learning and Blockchain to unlock the next stage of digitalization for traditional businesses. Our handpicked team is adept at web enterprise development, mobile apps, QA and DevOps. Sila, Cuentas, Youtility, Porsche, MGM Grand, Deloitte, Grindr, and Tawk.to are some of the top clients that have entrusted us to enhance their digital capabilities and build disruptive innovations. We believe in making the impossible, Possible and we do it literally.

Job Summary:

We are seeking a highly skilled Lead Data Engineer to design, implement, and optimize our data infrastructure with a focus on building robust, scalable data pipelines and ensuring seamless systems integration. The ideal candidate will excel in ETL/ELT processes, data orchestration using tools like Airflow, Prefect, or Dagster, and have experience with cloud platforms such as AWS or Azure. This role requires collaboration with cross-functional teams to support data analytics, business intelligence, and the broader data strategy.

Key Responsibilities:

• Data Pipeline Development: Design, develop, and manage complex data pipelines and workflows using tools like Airflow, Prefect, or Dagster, with an emphasis on modularity, scalability, and reliability.
• Data Integration: Establish and maintain integrations across APIs and diverse data sources, ensuring data integrity, accuracy, and consistency across platforms.
• ETL/ELT Processes: Develop and optimize ETL/ELT processes to transform and load data from multiple sources into cloud data warehouses such as Redshift, BigQuery, and Snowflake.
• Cloud Infrastructure: Deploy, monitor, and maintain data solutions on cloud platforms (e.g., AWS, Azure) to ensure scalability, security, and resilience.
• Tooling Automation: Leverage tools such as Astronomer, Fivetran, Stitch, and DBT to automate workflows, streamline data operations, and enhance data processing efficiency.
• Collaboration: Partner closely with data scientists, analysts, and stakeholders to gather requirements, understand data needs, and deliver optimized solutions.
• Performance Optimization: Monitor pipeline performance, troubleshoot issues, and implement enhancements to improve efficiency, reliability, and reduce latency.

Required Skills and Qualifications:

• Technical Proficiency:
• Advanced skills in Python for scripting and data processing.
• Proficient with ETL/ELT tools and orchestration frameworks, such as Airflow, Prefect, Dagster, or Fivetran.
• Hands-on experience designing and managing complex, multistage workflows.
• Expertise with cloud platforms (AWS, Azure) in deploying and managing scalable data solutions.
• Proficient in using Astronomer, DBT, or similar tools for workflow automation and data transformation.
• Database Management: Skilled in cloud data storage solutions, specifically Redshift, BigQuery, and Snowflake.
• API Data Integration: Proven experience in integrating APIs for data ingestion and ensuring data consistency across diverse systems.
• Analytical Thinking: Strong problem-solving abilities to troubleshoot pipeline issues, optimize workflows, and improve data processing efficiency.
• Communication Skills: Clear communication of technical concepts to both technical and non-technical team members and effective collaboration skills.

Preferred Qualifications:

• Certifications: Relevant AWS or Azure certifications in data engineering or cloud computing are advantageous.
• Experience with Modern Data Stack: Familiarity with tools like Stitch, Matillion, Hevo Data, Apache NiFi, or Singer for data integration, and Spark, Hadoop, and Hive for distributed data processing is beneficial.