• Application Deadline:
• Position: Data Lake Implementation Specialist



• Job Type Remote



• Qualification BA/BSc/HND



• Experience



• Location




• Job Field ICT / Computer 
  
  




• Salary Range ₦500,000 - ₦750,000/month
  
  

We are seeking an EXPERIENCED Data Lake Implementation Specialist to be responsible for guiding the setup and/or integration of on-premises and cloud data lakes to enable real-time analytics and AI in medium to large digital businesses. Experience in Apache Doris is an added advantage.

Core Skills & Expertise

Data Lake Architecture (Hybrid & Multi-Cloud)

1. Designing modern data lakehouses with raw + curated layers, unified batch + streaming ingestion


2. Integration with enterprise systems and support for schema-on-read


3. Familiarity with lakehouse tools: Delta Lake, Apache Iceberg, Hudi

Real-Time Data Processing

1. Expertise with streaming architectures: Apache Kafka, Flink, Spark Streaming


2. Experience with event-driven design, CDC, and real-time ETL tool


3. Delivered at least one large-scale Doris-based or comparable OLAP system in production


4. Tools: Debezium, StreamSets, Apache NiFi

Cloud & On-Prem Data Services

1. Cloud: AWS (S3, Glue, EMR, Kinesis), Azure (ADLS Gen2, Synapse), GCP (BigLake, Dataflow)


2. On-prem: Hadoop, Cloudera, MapR, private cloud environments

AI/ML Enablement

Data Preparation for AI/ML

1. Building pipelines for feature extraction and versioning datasets


2. Integration with feature stores and data quality enforcement

• ML Ops Readiness

1. Integration with ML pipelines (Kubeflow, MLflow, SageMaker)


2. Model deployment, tuning, and monitoring at scale

Analytics & BI Integration

1. Support for BI tools (Power BI, Tableau) and fast querying layers (Presto, Trino)


2. Near real-time dashboard enablement

Governance, Observability, and Security

Enterprise Data Governance

1. Implementing data ownership, lineage, and access policies


2. Use of catalogs: Collibra, Apache Atlas, AWS Glue Catalog

Observability & Monitoring

1. End-to-end pipeline visibility, logs, and metrics


2. Tools: Prometheus, Grafana, OpenTelemetry, Monte Carlo

Security & Compliance

1. Encryption, tokenization, and data masking


2. Adhering to regulations: GDPR, HIPAA, SOC2

Execution Experience

Large-Scale Implementations

1. Hands-on delivery of hybrid data lake architectures


2. Experience with syncing on-prem and cloud data systems

Cross-Functional Leadership

1. Working with data scientists, product teams, and security teams


2. Leading data platform teams or Centers of Excellence

Agility at Scale

1. Agile delivery models for data initiatives


2. Delivering data products and ML capabilities incrementally

Ideal candidate profile summary

A hands-on and strategic data lake architect/engineer with deep knowledge of hybrid and multi-cloud systems, proven experience with streaming data and ML enablement, and the leadership to orchestrate teams around real-time analytics and decision intelligence for digital enterprise scale.

Bonus: Certifications & Tools

Certifications

1. AWS/GCP/Azure Data Engineer or ML Engineer


2. Databricks Lakehouse Accreditation


3. CDMP or DAMA certification

Tools Stack

1. Airflow, dbt, Spark, Flink, Kafka


2. Terraform, GitOps, CI/CD


3. MLflow, Feature Store, SageMaker, Vertex AI


4. Apache Ranger, Atlas, Lake Formation