Lead Data Engineer
2 days ago
Description :
Primary Job Title : Data Engineering Lead.
About The Opportunity :
We are seeking a highly skilled Lead Data Engineer with strong expertise in Python, Pandas, PySpark, AWS, and SQL to design, build, and manage scalable data solutions.
The ideal candidate will lead a team of data engineers, develop robust ETL pipelines, and collaborate with analytics, data science, and business teams to ensure high data quality and performance across cloud-based environments.
Role & Responsibilities :
- Lead the design and development of data pipelines for ingestion, transformation, and integration from multiple sources into the enterprise data platform.
- Implement data quality frameworks, validation checks, and monitoring solutions using Python and SQL.
- Optimize PySpark jobs for performance and scalability in a distributed computing environment (AWS EMR/Glue).
- Develop reusable ETL frameworks using PySpark and Pandas for data transformation and analytics.
- Manage and maintain cloud-based infrastructure and data storage (AWS S3, Redshift, Lambda, Glue, Athena).
- Collaborate with data scientists, analysts, and stakeholders to provide clean, structured, and accessible datasets.
- Oversee code reviews, performance tuning, and mentoring junior data engineers.
- Establish best practices for data governance, version control, and CI/CD integration.
- Troubleshoot production data issues and ensure system reliability, availability, and efficiency.
Must-Have Skills :
- Programming : Python (advanced scripting, Pandas, PySpark).
- Cloud : AWS (S3, Glue, Lambda, Redshift, Athena, EMR).
- Database / Querying : Advanced SQL (Joins, Window Functions, Query Optimization).
- Big Data Tools : PySpark, Spark SQL.
- ETL Development : Data ingestion, transformation, and validation pipelines.
- Version Control : Git / GitHub / Bitbucket.
- Workflow Orchestration : Apache Airflow or equivalent (preferred).
Good-to-Have Skills :
- Experience with Docker or Kubernetes for containerization.
- Familiarity with CI/CD pipelines and DevOps practices.
- Exposure to data modeling, schema design, and partitioning strategies.
- Understanding of data lake and data warehouse architecture.
- Knowledge of monitoring tools (CloudWatch, Datadog, or Prometheus).
Qualifications :
- Bachelors or Masters degree in Computer Science, Data Engineering, or a related field.
years of total experience with at least 3- 4 years leading data engineering projects.
- Proven track record in handling large-scale data pipelines and cloud migrations.
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