Data Engineer / Developer

The purpose of this role is to develop required software features, achieving timely delivery in compliance with the performance and quality standards of the company.

Job Description:

Technical Skills

• Data Cleaning Tools & Libraries: Proficiency with tools and libraries to clean and preprocess data for example:
  • Python
  • R
  • SQL
  • Excel- emphasis on Familiarity with data cleaning functions, filters, and pivot tables.

2. Data Management & Analysis Skills

• Data Validation & Consistency: Ability to identify data quality issues such as duplicates, missing values, outliers, and inconsistencies.
• Data Transformation: Experience in transforming raw data into usable formats, including reshaping, aggregating, or normalizing data.
• Handling Missing Data: Familiarity with imputation techniques or ways to deal with incomplete datasets.
• Data Normalization & Standardization: Ensuring uniformity in data formats, units of measurement, and naming conventions.
• Data Aggregation: Summarizing or grouping data for analysis and ensuring that it is consistent across all sources.

3. Knowledge of Data Quality

• Data Integrity: Understanding the importance of maintaining accurate and consistent data over time.
• Data Profiling: Identifying patterns, anomalies, and key characteristics of the dataset.
• Error Detection: Ability to find and correct errors within datasets by checking for outliers, misclassifications, or missing values.

4. Soft Skills

• Attention to Detail: The ability to identify small inconsistencies and issues within large datasets.
• Problem-Solving: Being resourceful in resolving data issues and proposing solutions.
• Critical Thinking: Analyzing data in-depth and understanding its implications.
• Communication: Ability to explain data issues and cleaning steps to non-technical stakeholders.

5. Experience with Data Formats

• Structured Data: Familiarity with both structured (tables, databases)
• Data Sources: Ability to clean data from various sources such as spreadsheets, databases, APIs, logs, etc.
• File Formats: Proficiency in working with common data file formats like CSV, XML, and Excel.

6. Statistical and Analytical Skills

• Basic Statistics: Understanding of basic statistical concepts to spot anomalies, outliers, or trends in data.
• Data Visualization: Ability to visualize the cleaned data to identify trends and patterns (e.g., with Power BI .

7. Automation and Scripting

• Automating Repetitive Tasks: Experience in automating data cleaning processes with scripts or workflow automation tools.
• Batch Processing: Capability to clean data in bulk, particularly when dealing with large datasets.

Location:

DGS India - Pune - Extentia Tower

Brand:

Merkle

Time Type:

Full time

Contract Type:

Permanent