About Us

About DATAECONOMY: We are a fast-growing data & analytics company headquartered in Dublin with offices inDublin, OH, Providence, RI, and an advanced technology center in Hyderabad,India. We are clearly differentiated in the data & analytics space via our suite of solutions, accelerators, frameworks, and thought leadership.

Job Description

We are seeking a Lead ETL Data Engineer to design, develop, and optimize data pipelines, ensuring smooth data integration across our platforms. This role will lead a team of ETL developers and work closely with data analysts, engineers, and business stakeholders to drive data solutions in a cloud environment.

Key Responsibilities

✅ ETL Development & Data Pipeline Design

• Lead the design, development, and optimization of ETL processes using Talend (or similar ETL tools).
• Build, automate, and maintain scalable data pipelines for efficient data processing.
• Ensure data quality, consistency, and performance across ETL workflows.
  
  

✅ Database & Data Warehouse Management

• Work with relational and NoSQL databases, ensuring optimized SQL queries for performance.
• Implement data warehouse solutions (DWH) on AWS (Redshift, S3, Glue, RDS) or other cloud environments.
• Perform data modeling to support business intelligence and analytics.
  
  

✅ Leadership & Collaboration

• Guide and mentor a team of ETL developers and data engineers.
• Collaborate with data scientists, analysts, and business teams to understand data needs.
• Drive best practices in data governance, security, and compliance.
  
  

✅ Performance Optimization & Troubleshooting

• Monitor and troubleshoot ETL performance issues.
• Optimize database performance and ensure low-latency data processing.
• Automate error handling and data recovery strategies.
  
  

Requirements

Required Skills & Qualifications:

✔ 10+ years of experience in ETL development and data engineering.

✔ Expertise in ETL tools like Talend, Informatica, or Apache NiFi.

✔ Strong proficiency in SQL and database optimization techniques.

✔ Hands-on experience with AWS cloud services (Redshift, Glue, Lambda, S3, RDS, etc.).

✔ Experience with big data technologies (Spark, Hadoop, or Kafka) is a plus.

✔ Solid understanding of data modeling, warehousing (DWH), and governance.

✔ Excellent problem-solving and communication skills.

✔ Experience in leading a team and driving technical best practices.

Benefits

As per company standards.