Accountant II - Data & Automation

EchoStar•Littleton, CO

About The Position

The General Ledger team seeks a highly analytical accountant to improve the accuracy and efficiency of the month-end close. The role combines accounting expertise with data, automation, and AI to streamline manual reconciliations and recurring close tasks. It manages daily general ledger operations, strengthens data validations and controls, and helps provide real-time visibility into close status and account health. The Accountant II works with FP&A, Data Engineering, IT, and business teams to evolve Boost's accounting systems, data tools, and AI capabilities. The role also performs financial analysis to support strategic initiatives and new products, and translates complex data and accounting concepts into actionable insights for non-financial partners.

Requirements

Bachelor's degree in Accounting, Accounting Information Systems, or a quantitative field such as Data Science/Analytics, Computer Science, Statistics, Mathematics, or Economics; accounting coursework is required for non-accounting degrees.
One to three years of accounting experience, including internships, co-ops, or relevant academic projects.
At least two years of experience with general ledger accounting under US GAAP, including accruals, reconciliations, and month-end close.
At least two years of experience using SQL or Python to pull and reconcile general ledger and subledger data.
At least two years of experience using AI tools such as Copilot or Amazon Quick with SOX and audit-trail controls in mind.
Solid understanding of GAAP, double-entry accounting, and the close cycle.
Advanced Excel skills.
Self-motivation, creative problem-solving skills, and strong attention to detail.
Excellent communication skills, including the ability to explain financial and data findings to non-financial partners.
Curiosity, eagerness to learn a complex and changing business, adaptability, and comfort working in a fast-paced environment.
Willingness to participate in at least one in-person interview.

Nice To Haves

Master's degree in Accounting (MAcc), Accounting Analytics, Business Analytics, or Data Science.
Working knowledge of SQL and/or Python.
Familiarity with Databricks; Snowflake, BigQuery, or a similar platform is also considered.
ERP exposure such as Oracle, SAP, or NetSuite.
Familiarity with generative AI assistants, Databricks AI features, Amazon Quick, and Copilot, and interest in applying them to accounting.

Responsibilities

Manage daily general ledger operations, including preparing journal entries and reconciling accounts, to ensure financial data is accurate and complete.
Contribute to month-end and year-end close processes, meet deadlines, and investigate and resolve accounting discrepancies through root-cause analysis.
Identify opportunities to automate manual reconciliations, journal-entry support, and recurring close tasks using tools such as Databricks, Amazon Quick, Copilot, SQL, and Python.
Identify and help adopt AI-driven accounting solutions, including reconciliation matching, variance and flux commentary, anomaly detection, and documentation.
Use data analysis on large datasets to strengthen data validations and controls and improve account-balance accuracy.
Help build and maintain data workflows that provide real-time visibility into close status and account health.
Work with FP&A, Data Engineering, IT, and business teams on data requirements and upstream processes that feed the general ledger.
Translate complex data into actionable insights, explain accounting concepts in terms of underlying data, and perform financial analysis to support strategic initiatives and new products.