Data & Analytics Lead

Evolution Recruitment Solutions PTE. LTD.

Singapore

On-site

SGD 180,000 - 260,000

Full time

5 days ago
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Job summary

Evolution Recruitment Solutions PTE. LTD. seeks a senior data engineering leader to drive development and deployment of enterprise analytic data products. You will shape data product strategy, partner with analytics, data science, product, and engineering, and guide a geographically distributed team.

You will own scalable production software across Python/Java, streaming pipelines (Kafka/Spark), and cloud data platforms, while mentoring staff and aligning solutions with business goals.

Qualifications

  • Extensive experience building and leading data engineering teams in an enterprise environment.
  • Ability to collaborate with analytics, data science, product and engineering to align with business goals.
  • Experience establishing forums and representing data engineering in cross-team settings.
  • Strong fundamentals in engineering, architecture and system design.
  • Proficiency developing scalable production software in Python/Java.
  • Experience with event-driven or streaming pipelines using Kafka and Spark.

Responsibilities

  • Lead development and deployment of enterprise analytic data products and pilots.
  • Design strategies and methodologies for data products with enterprise impact.
  • Execute data strategies considering enterprise architecture and platforms.
  • Build partnerships to align data solutions with business objectives.
  • Communicate complex tech concepts to non-technical stakeholders.
  • Collaborate with security teams to protect sensitive data.
  • Mentor team members and drive technical excellence.

Skills

Data engineering leadership
Strategic partnerships
Python
Java
Kafka
Spark
SQL
NoSQL
Cloud platforms
Databricks
ETL pipelines
Data warehousing
Team coaching
Cross-functional collaboration
Communications

Education

Bachelor's or Master's in Computer Science

Tools

Azure
Databricks
Python
Java
Kafka
dbt
Terraform
Snowflake
SQL
Jenkins
Github
Airflow
MLFlow

Job description

Primary Job Duties & Responsibilities

  • Lead development and production deployment of enterprise-level analytic data products (also potentially pilots and proof of concepts), determining appropriate design strategies and methodologies.
  • Find creative solutions to challenging problems involving factors with potentially broad implications; reflecting on solutions, measuring impact, and using that information to ideate and optimize.
  • Execute data strategies with an understanding of enterprise architecture, consumption patterns, platforms and application infrastructure.
  • Develop business partnerships and influence priorities by identifying solutions that are aligned with current business objectives and closely follow industry trends.
  • Communicate with partners, describing technology concepts in ways the business can understand, documenting initiatives in a concise and clear manner, and empathetically and actively listening to other's thoughts and ideas.
  • Partner with data management & information security colleagues to ensure the protection of highly sensitive datasets.
  • Maintain relationships with partner teams to ensure needs are met and impacted areas plan work accordingly.
  • Present analysis and recommendations to help influence strategic decisions.
  • Lead and take action, inspire and motivate others, and be effective at influencing team members.
  • Guide and coach team members, focusing on individual's professional development as well as overall team health and technical proficiency.

What Will Our Ideal Candidate Have

  • Preferably 10+ years of work experience building, managing, and leading high-performing, diverse, collaborative, and geographically distributed data engineering teams.
  • Demonstrated ability as a strategic technical partner, working collaboratively with data analytics, data science, product, engineering, and other cross-functional partners, to plan, prioritize, and achieve company goals.
  • Experience starting, leading, and evolving technical forums, with effective soft skills, as well as representing data engineering and architectural considerations in cross-team settings.
  • Experience developing and nurturing data engineering talent, including implementing training, upskilling, and mentorship plans. Expert-level engineering, architecture, and system design knowledge, with strong computer science fundamentals.
  • Experience developing efficient and scalable production software in Python, Java, or other programming languages commonly used in data engineering
  • Understanding of event-driven and/or streaming workflows with tools like Kafka and Spark Aptitude with ETL concepts and tools, including experience ingesting, processing, and transforming a variety of data at scale Proficiency with SQL and NoSQL databases, data warehousing concepts, and cloud-based analytics databases.
  • Experience with some of the following tools & platforms (or similar): Azure (ADLS, ADF, AKS, Synapse, Purview), Databricks, Python, Java , Kafka, dbt, Terraform, Snowflake, SQL, Jenkins, Github, Airflow, MLFlow Knowledge and experience with the some of the following concepts: Real-time & Batch Data Processing, Workload Orchestration, Cloud, Datalakes, Data Security, Networking, Serverless, Testing / Test Automation (Unit, Integration, Performance, etc.), WebServices, DevOps, Logging, Monitoring, and Alerting, Containerization, Encryption / Decryption, Data Masking, Cost & Performance Optimization.
  • Excellent written and oral communication skills, with a demonstrated ability to communicate complex concepts to a wide range of audiences.
  • Ability to thrive in a fast-paced, agile, and dynamic environment, while exuding a can-do attitude Ability to handle multiple concurrent projects while working independently and in teams of all sizes with representatives from a diverse set of technical backgrounds.
  • Bachelor's or Master's degree in Computer Science or equivalent; team leadership and management training is a plus.
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