Data Engineer Job at DAG Industries Nigeria Limited

DAG Industries

Ikeja, Lagos State
Permanent
Full-time

18 days ago
Apply easily

DAG Industries Nigeria Limited - We provide the most popular range of Bajaj motorcycles, Bajaj tricycles, Bajaj genuine spares, MRF tyres, DAG lubricants and unfaltering after sales service. Backed by its untiring team of professional and trained technicians, authorized service stations and its own service center, DAG has been instrumental in developing Nigeria through building infrastructure and creating jobs thereby providing a livelihood for the common people in Nigeria. We at DAG are committed to provide genuine spare parts, accessories, and a never failing support to its customers and business associates.We are recruiting to fill the position below:Job Position: Data EngineerJob Location: Ikeja, Lagos
Employment Type: Full-time (hybrid)
Department: Digital & Data
Reports to: Chief Digital OfficerWhy This Role Exists

DAG Industries Nigeria is digitizing. You’ll build reliable data pipelines and models that turn raw data into trustworthy, analytics-ready datasets—fuelling decisions across the business in real time.

Responsibilities
What you’ll do:

Own data pipelines end-to-end: Design, build, and maintain batch pipelines for all business units.
Model the data: Implement robust data models that support BI, ML, and operational use cases.
Manage storage layers: Create modern data lakes/lakehouses and warehouse schemas; ensure efficient partitioning, compaction, and cost control.
Harden data quality: Implement tests, contracts, and observability (lineage, metadata, SLAs).
Secure & govern: Apply best practices for IAM, data masking, encryption, and compliance with NDPR and company policies.
Collaborate & enable: Partner with our business units to define datasets, publish documentation, and enable self-service.
Automate the platform: Use CI/CD and Infrastructure-as-Code to provision and maintain data infrastructure reliably and use tools for workflow orchestration.
Continuously improve: Profile workloads, tune jobs, and reduce costs while improving reliability and performance.

Must-Have Skills & Experience:

Programming Languages: Proficiency in Python, Java, or Scala (one or more).
Database Management: Strong SQL and hands-on experience with both relational (e.g., Postgres, MySQL, SQL Server) and NoSQL stores (e.g., MongoDB, Cassandra, DynamoDB).
ETL/ELT Processes: Proven experience designing and operating Extract–Transform–Load workflows (batch and streaming).
Data Modelling: Solid grasp of data modelling concepts and techniques (OLTP vs. OLAP, dimensional modelling, normalization).
Automation: experience in creating automation with scripting and Microsoft Power Apps.
Cloud Computing: Working knowledge of AWS, Azure, or Google Cloud services for data engineering (e.g., S3/ADLS/GCS, EMR/Databricks/Synapse/BigQuery, MSK/Kinesis/Pub/Sub).
Big Data Technologies: Practical familiarity with Hadoop, Spark, and Kafka.
Foundations: Git, Linux, containers; writing production-grade, testable code; clear documentation.

Nice to have:

Airflow/Dagster orchestration expertise; dbt for transformations.
Knowledge about lakehouse patterns (Delta/Apache Hudi/Iceberg) and columnar formats (Parquet).
Data quality/observability tooling (Great Expectations, Monte Carlo, OpenLineage).
CI/CD (GitHub Actions, GitLab CI, Azure DevOps) and IaC (Terraform, CloudFormation).
BI exposure (Power BI, Looker, Tableau, Qlik Sense) and ML feature pipelines (Feast, Tecton) a plus.
Domain experience in automotive, aftermarket, logistics, or multi-site service networks.

Requirements
Education & Experience:

Bachelor’s degree in Computer Science, Engineering, Mathematics, or equivalent practical experience.
3–7+ years in data engineering (title/level will align with experience and scope).

Method of Application
Interested and qualified candidates should send their CV to: using the Job Position as the subject of the mail.

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