We are seeking an experienced, leadership-driven Data Engineer to lead our data infrastructure team and maintain the highest standards of data pipeline reliability, architectural scalability, and performance optimization. In this senior role, you will oversee all aspects of our data ecosystem, including ingestion, storage, processing, and delivery of high-quality data to stakeholders. If you have strong team leadership skills, deep knowledge of modern data engineering practices, and a passion for operational excellence and robust data systems, this is an outstanding opportunity to shape the technical backbone and analytical performance of our organization.

Key Responsibilities
Team Leadership: Manage, mentor, motivate, and evaluate the entire data engineering team, including junior/senior engineers, database administrators, and pipeline developers.

Standards & Quality Control: Establish and enforce high coding standards, architectural patterns, and data quality frameworks; conduct regular code reviews and infrastructure audits.

Operations Planning: Develop and manage sprint cycles, technical roadmaps, and infrastructure scaling plans to ensure efficient data ingestion and low-latency delivery.

Resource & Budget Management: Control cloud data infrastructure costs (e.g., Snowflake, BigQuery, Databricks), software licensing, and development tool budgets; manage relationships with cloud vendors.

Stakeholder Collaboration: Collaborate with Data Science, Product, and Analytics teams to translate business requirements into efficient, scalable, and secure data pipelines.

Training & Development: Design and deliver comprehensive training programs on new data technologies, ELT/ETL best practices, and data governance; mentor team leads and engineers.

Compliance & Reliability: Ensure full adherence to data privacy regulations (e.g., GDPR, CCPA), security standards, and internal corporate data governance guidelines.

Reporting & Continuous Improvement: Prepare reports on data pipeline performance, latency, and throughput; implement CI/CD for data and innovative big data processing methodologies.

Requirements & Qualifications
Education: Bachelor’s degree in Computer Science, Software Engineering, Data Engineering, or a related field is preferred.

Experience: 5–10+ years in software or data engineering, with at least 3–5 years in a technical leadership or management capacity. Experience in architecting large-scale data platforms is highly desirable.

Technical & Management Skills:

Strong knowledge of SQL, NoSQL, data warehousing, and cloud data platforms (e.g., AWS, GCP, Azure).

Experience with big data frameworks (e.g., Apache Spark, Kafka, Airflow) and CI/CD pipelines.

Proven ability to lead high-performing teams and optimize end-to-end data lifecycles.

Soft Skills:

Excellent leadership, communication, and interpersonal skills.

Strong problem-solving, decision-making, and organizational abilities.

High attention to detail with a focus on data integrity and system scalability.

Ability to work under pressure and manage multiple technical priorities in a dynamic environment.

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