Senior Data Analyst / Data Engineer

The Senior Data Analyst / Data Engineer will support the analysis, transformation, correlation, and standardization of EMAT and standard ILI pipe tally datasets across approximately. This resource will work under the direction of the Technical Lead to profile data, execute matching and transformation logic, identify exceptions, and produce validated outputs in a consistent, auditable format for client use.

This role is best suited for a hands-on resource with strong experience in data wrangling, structured file comparison, data quality analysis, and repeatable transformation execution, ideally within engineering, industrial, or utility data environments.

Key Skills

Data profiling and analysis

File comparison and reconciliation

Data cleansing and transformation

Structured problem solving

Exception identification and documentation

Python / SQL / Excel-based data handling

Quality control and auditability

Attention to detail

Ability to execute repeatable processing with consistency

Clear technical documentation

Ideal Candidate Profile

The ideal candidate is a strong hands-on data specialist who can work through complex file structures, identify patterns and mismatches, and execute a repeatable transformation process with high accuracy. They should be comfortable operating in a partially defined environment, where discovery and iteration are required before the final approach is fully established., 5+ years of experience in:

Data analysis

Data engineering

Data transformation/preparation

Data quality analysis

Engineering or industrial data support

Experience working with large structured datasets in flat files, spreadsheets, CSVs, or database extracts.

Experience identifying and reconciling data discrepancies across multiple source files.

Experience performing repeatable data transformations and documenting assumptions/logic.

Strong working knowledge of tools such as:

Python

SQL

Excel / Power Query

Similar data manipulation tools

Experience supporting validation, exception handling, and output quality review. Experience with:

Pipeline inspection data

Pipe tally records

EMAT or in-line inspection datasets

Engineering asset or inspection data

Utility, energy, or industrial operations datasets

Exposure to data correlation problems involving distance-based or linear asset records.

Experience supporting data preparation for database integration or enterprise platforms.

Familiarity with working in environments where source data lacks standardization or formal documentation.