Senior Data Engineer
Madison Logic
Job Summary
Madison Logic is seeking a Senior Data Engineer to play a key role in developing its data and analytics capabilities. The role involves designing, building, and deploying scalable data pipelines and creating APIs for machine learning products. Responsibilities include refining data models, collaborating with product and engineering teams, writing production-level SQL and Python code, conducting data analysis, identifying optimal data sources, establishing data mining procedures, and collaborating with partners. The position requires a Bachelor's degree in computer science, statistics, or mathematics, with a minimum of 5 years of experience in Python and SQL, 3 years in AWS, and experience with data architectures like Kafka, Data Warehouses, and ODS. Knowledge of cloud analytics platforms like Snowflake and AWS SageMaker is also important.
Must Have
- 5+ years of experience with Python
- 5+ years of experience in SQL
- 3+ years of experience with AWS
- Experience designing data architectures
- Fluent in English (verbal and written)
- Bachelor's degree in CS, Statistics, or Math
Good to Have
- Experience with Airflow
- Experience with data workflow management tools
- Skilled in data cleaning and standardization
- Understanding of SQL engines and performance tuning
Perks & Benefits
- 5 LPA Medical Coverage
- Life Insurance
- Provident Fund Contributions
- Learning & Development Stipend
- Wellness Stipend
- Transportation for female team-members (specific shifts)
- Welcoming in-office environment
Job Description
- Develop and maintain the core data pipelines, involving the creation of production-level SQL and Python code to fuel our platforms.
- Adapt and enhance data models and data schemas to align with both business and engineering requirements.
- Conduct data analysis to contribute to the enhancement of overall business performance.
- Identify and select optimal data sources for specific analytical tasks.
- Establish procedures for data mining, data modeling, and data production.
- Collaborate with internal and external partners to address challenges and ensure successful outcomes.
- On-site working at the ML physical office, 5-days per week is required through the end of probation (6 months), transitioning to 2-day WFH post-probation.
- Ability to work UK Shift Timing (11:00am – 8:00pm Local Time) Required
- Fluent in English language (verbal and written) and possessing a clear and concise communication style.
- Educational Background: Possess a Bachelor's degree in computer science, statistics, or mathematics.
- Programming Expertise: 5+ years of experience with Python, with the ability to write production-level code.
- SQL Proficiency: 5+ years of experience in SQL, with excellent skills in navigating multiple data tables and comprehending data models.
- Cloud Computing: 3+ years of hands-on experience with cloud computing services, particularly AWS (Amazon Web Services).
- Data Architecture: Proven experience in designing data architectures, including Kafka, Data Warehouses and Operational Data Stores (ODS).
- Cloud-Based Analytics: Possess a strong understanding of cloud-based analytics platforms, such as Snowflake and AWS SageMaker.
- Data Workflow Management: Ideally, possess at least 1 year of experience with data workflow management tools, with Airflow experience being a plus.
- Data Cleaning: Be skilled in data cleaning and standardization processes.
- SQL Engine: Exhibit an excellent understanding of SQL engines and the capability to perform advanced performance tuning.
- Self-Sufficient and proactive nature, able & comfortable "figuring things out", resorting to escalation only when after exhausting all other options
- Strong sense of urgency required
- Exceptional communication skills, both verbal and written, with a knack for explaining complex concepts in a clear & concise manner across all levels and functions
- Team members are encouraged to work collaboratively with an emphasis on results, not on hierarchy or titles.
- 5 LPA Medical Coverage
- Life Insurance
- Provident Fund Contributions
- Learning & Development Stipend (Over-And-Above CTC)
- Wellness Stipend (Over-And-Above CTC)
- Transportation available for female team-members with shifts starting or ending between the hours of 9:30pm and 7:00am
- Welcoming in-office environment (located within AWFIS co-working space, Amanora Mall)
- Team members are encouraged to work collaboratively with an emphasis on results, not on hierarchy or titles.