Data Leader
MYMIND
Mô tả công việc
ABOUT THE COMPANY With over 10 years of relentless innovation, MyMind Joint Stock Company (MSM) is redefining the future of enterprise management. We deliver smart, scalable digital solutions that power business transformation across industries—from enterprises and agriculture to smart manufacturing. By combining deep domain expertise with cutting-edge technology, MSM helps organizations worldwide simplify complexity, accelerate growth, and lead with confidence in the digital era.
Yêu cầu công việc
ABOUT THE POSITION The Data Leader owns the data function at MSM end-to-end: the data platform (lake, warehouse, DaaS), the data team, and the alignment between data and the business domains we serve — Ecommerce, ERP/DMS, and AgriTech. The role is hands-on at the architecture level while being accountable for people, delivery, and standards. 1. Responsibilities a. Team leadership & mentoring Lead, coach, and mentor the data engineering team (Senior/Middle/Junior); run 1:1s, define growth paths, and conduct performance reviews. Set technical standards through design reviews, code reviews, and pairing — raise the team's bar rather than doing all the hard work alone. Build the hiring pipeline: define role profiles, interview, and onboard data engineers and analysts. b. Resource coordination & delivery Plan, allocate, and rebalance team capacity across squads/projects (DigiRetail, DigiFarm, DigiFactory, DigiO) based on priority, risk, and deadlines. Own the data roadmap and backlog — break business requests into epics/stories, estimate effort, track delivery, and report status to management and stakeholders. Manage cross-team dependencies with product, backend, DevOps, and data science; unblock the team and escalate early. c. Business & domain alignment Understand the business data models of Ecommerce (orders, catalog, inventory, promotions, customer/CRM/CDP), ERP/DMS (sales-distribution, finance, procurement, warehouse), and AgriTech (field, crop, GIS, IoT/sensor). Translate business KPIs into data products: define metrics, dimensional models, and data contracts with product owners and domain experts. Act as the primary data counterpart for stakeholders (Product, Finance, Operations, Customers/Partners) — and own data governance, data quality, and access policies. d. Platform & architecture Architect and evolve the data platform: batch/streaming pipelines, data lake/lakehouse, warehouse, and DaaS/API layers for analytics, applications, and partners. Develop and maintain GIS data systems enabling geospatial analytics and field-level monitoring. Optimize storage and compute cost/performance across on-premise and cloud; enforce infrastructure-as-code, versioning, and reproducibility. Drive AI/ML enablement on the platform: feature pipelines, model serving integration, and AI- ready data architecture (advantage — see Nice to Have). 2. Requirements a. Must Have Skills Experience: 7+ years in data engineering / data platform, including 2+ years leading a data team (3+ members) with direct people-management responsibility. Leadership & mentoring: proven track record of growing engineers, running design/code reviews, and setting team standards. Resource & delivery management: capacity planning, prioritization, estimation, and status reporting across multiple concurrent projects; hands-on with Jira/agile delivery. Business domain knowledge: solid understanding of Ecommerce and/or ERP/DMS data (transactional models, master data, KPIs, reconciliation, reporting needs); experience working directly with business stakeholders. Core technical skills: Proficient in Python and SQL for data transformation and automation. Strong experience with distributed processing frameworks(e.g.,Apache Spark, Flink). Experience designing and operating data lakes/lake houses and warehouses(e.g.,Iceberg, Delta Lake, BigQuery, Redshift). Experience designing APIs or DaaS platforms for data delivery. Solid knowledge of data modeling (Kimball, DataVault, or similar) and data governance/quality frameworks. Familiarity with semi-structured and unstructured data (JSON, geospatial, IoT, sensor data). Tools/Software proficiency: Orchestration tools(Airflow, Dagster, Prefect). Cloud platforms(AWS preferred; GCP or Azure). Git, CI/CD, and infrastructure-as-code(Terraform or equivalent). b. Nice to Have Skills AI Engineer experience (strong advantage): designing AI/ML architecture on AWS — e.g., SageMaker, Bedrock, Lambda/Step Functions, feature store, vector databases, model serving/MLOps — and integrating AI into data pipelines (data enrichment, anomaly detection, predictive modeling for AgriTech/Ecommerce use cases). Education: Bachelor's or Master's in Computer Science, Data Engineering, or related fields. Mindset: practical, detail-oriented, collaborative, and curious about how data can improve agriculture and retail operations. Advanced tools/technology skills: Geospatial tools and libraries (PostGIS,GeoPandas,QGIS). Data catalog or governance tools(OpenMetadata, DataHub). Streaming platforms(Kafka,Pulsar). Semantic/BI layer and self-service analytics(dbt, Metabase, PowerBI, orsimilar). • Certifications: AWS Certified Data Engineer / Solutions Architect / Machine Learning Specialty.
Quyền lợi
WHAT'S ON OFFER A chance to work in the fast-growing and innovative AgriTech sector, solving meaningful problems that impact farmers and sustainability. An opportunity to lead and build the data function from the ground up, shaping architecture, team, tools, and standards for the future. A collaborative and learning-focused environment. Competitive salary and benefits package. Personal Healthcare Insurance, Annual Healthcare checkup.... Company events: 8/3, 20/10, Men's Day, Mid-Autumn, Year End Party, Company Trip.... Bonus: 13th-month salary and performance bonus (subject to individual performance and the company's business results). Modern and well-equipped working facilities.