Data Engineering

The Director of Data Platform Engineering will lead the design, development, and management of the company’s data infrastructure. This role ensures that data platforms are scalable, secure, and reliable, supporting analytics, business intelligence, and machine learning initiatives. The ideal candidate has extensive experience in data engineering, team leadership, and cloud-based data solutions.

Key Responsibilities:
    •    Lead and manage the data engineering team, providing mentorship, guidance, and performance management.
    •    Design, implement, and maintain scalable data platforms that handle large volumes of structured and unstructured data.
    •    Collaborate with stakeholders, including data scientists, analysts, and product teams, to define data requirements and deliver solutions.
    •    Ensure data quality, integrity, and security across all platforms.
    •    Develop and enforce best practices for data engineering, including data modeling, ETL processes, and data governance.
    •    Evaluate and implement new technologies to improve data platform performance and scalability.
    •    Oversee the migration of legacy systems to modern cloud-based data platforms (e.g., AWS, Azure, GCP).
    •    Monitor platform performance and troubleshoot complex data issues.

Qualifications & Requirements:
    •    Bachelor’s or Master’s degree in Computer Science, Information Technology, or related field.
    •    10+ years of experience in data engineering or software engineering, with at least 3–5 years in a leadership role.
    •    Strong experience with cloud platforms (AWS, Azure, GCP) and big data technologies (Spark, Hadoop, Kafka, etc.).
    •    Expertise in SQL, Python, Java, or other programming languages for data processing.
    •    Experience with data warehousing solutions (Snowflake, Redshift, BigQuery, etc.) and ETL tools.
    •    Proven ability to lead cross-functional teams and deliver complex projects on time.
    •    Strong analytical, problem-solving, and communication skills.

Preferred Skills:
    •    Experience with machine learning pipelines and AI/ML platforms.
    •    Knowledge of data governance, compliance, and privacy regulations.
    •    Familiarity with microservices architecture and API-based data integration.

Benefits:
    •    Competitive salary and performance-based bonuses.
    •    Flexible work arrangements and remote options.
    •    Health, dental, and vision insurance.
    •    Professional development opportunities and mentorship programs.